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The potential of social media to disseminate, aggregate, channel and democratize social accountability processes has encouraged a variety of organizations to actively promote and champion such initiatives. These initiatives typically envision a three step social accountability process where, for example, the publication of previously-private financial information about the inappropriate wealth accumulation activities of politicians and their business allies (step #1), combined with social media dissemination and discussion of these activities (step #2), can result in an accountability conversation that spills out of the medium and that sometimes results in positive social change (step #3). The current study examines Twitter reactions to the International Consortium of Investigative Journalist’s (ICIJ) publication of the Panama Papers. The analysis illustrates that there was a Twitter reaction: furthermore, that there were different styles of response and that certain styles were more likely to elicit an audience reaction, especially if the tweeter was a journalist or organization. While the provided analysis focuses on step #2 within the social accountability process, the results imply that publicly-interested accounting academics qua activists can facilitate social accountability by helping to make previously-private financial information public and by cultivating sympathetic individuals within the traditional media as well as within organizations that are active on social media.

This study aims to investigate the altmetric activity of papers published by the University of Zagreb School of Medicine in internationally visible journals and to identify differences in altmetric activity between the papers published in international and local journals and between those published in English and Croatian. We also investigated changes in altmetric activity over time and the characteristics of papers with the highest Twitter and Mendeley activity. The sample included 390 papers collected from the bibliographic database Scopus. Their altmetric and citation activities were measured at three time points: in July 2014, 2015, and 2016. The findings generally correspond to those observed in the large-scale studies of medical papers. Papers in renowned journals, and papers reporting clinical guidelines and multicentric studies had the most intense altmetric activity. In contrast, papers published in local, Croatian journals showed minimal altmetric activity, especially the papers published in Croatian. These results indicate that the local publishing community has not yet recognised social media as a tool for promoting research and that non-English language publications have minimal chances to receive attention, even in social media. The evaluative potential of altmetric indicators has to be further explored in a broader context.

This document attempts to summarise some of the research conducted at the Allens Hub, which may assist the Commission in exploring issues relating to technology and human rights. We are aware that some of the research referred in our paper may relate to very specific topics, as they were not originally written for this paper. Nonetheless, we hope our research will aid the Commission in exploring issues relating to technology and human rights, particularly in the areas of social media regulations and AI-informed decision making. Overall, we are grateful for the opportunity to present our views and hope this paper will help the Commission in completing his final report.

Trust in institutions and political participation are both essential for democracy. This paper proposes modeling trust in institutions among 14-year-old students in schools comparatively using ICCS 2016 data from 13 European countries. Data include more than 54,000 students in their eighth grade of schooling. Based on previous studies, we hypothesize to find that social media harm trust in institutions and therefore negatively affect civic and democratic participation. Trust and civic culture systems are studied using SEM. Results indicate that trust in social media indeed negatively influences trust in institutions in almost all European countries, which in turn reduces expected political and electoral participation of students.

This paper explores the theoretical review of technological innovation on SME survival by looking at literature review with SME studies. Previous reference on survival is still scarce even it is the key benchmark to measure business performance. It has been demonstrated within the literature that the practice of technological innovation is significantly associated with business performance but its effect towards SME survival is underexplored. SME survival refers to the year of business operation, availability of future plans and diversity of product/service range. According to social scientists and management experts, among the main technological innovations highlighted in literatures are namely sophisticated machines and equipments, fusion of different technologies, gadgets machines and equipments, fusion of different technologies, and gadgets as tools of innovation. By looking at the technological innovation scope by Diaconu (2011) ; social networking, computerized record, online marketing can be categorized under the current technological innovation as these mediums are based on technology and influence the development intensity with new or improved process or products. Apart from this justification, among other approaches, these three mediums are close to the business and its potentials are yet to be optimized. In short, the critical discussion provided in this paper would help to strengthen the body of knowledge on SME studies, besides to act as a reference for research in other countries. Findings from this review shed some lights on the potential of social networking as part of online marketing; as the online customers are greater than the typical offline customers. Also, the effect of online marketing via social media is more powerful and diverse due to its ability to reach customers regardless of geographical locations.

In the current era of internet, information related to crime is scattered across many sources namely news media, social networks, blogs, and video repositories, etc. Crime reports published in online newspapers are often considered as reliable compared to crowdsourced data like social media and contain crime information not only in the form of unstructured text but also in the form of images. Given the volume and availability of crime-related information present in online newspapers, gathering and integrating crime entities from multiple modalities and representing them as a knowledge base in machine-readable form will be useful for any law enforcement agencies to analyze and prevent criminal activities. Extant research works to generate the crime knowledge base, does not address extraction of all non-redundant entities from text and image data present in multiple newspapers. Hence, this work proposes Crime Base, an entity relationship based system to extract and integrate crime related text and image data from online newspapers with a focus towards reducing duplicity and loss of information in the knowledge base. The proposed system uses a rule-based approach to extract the entities from text and image captions. The entities extracted from text data are correlated using contextual as-well-as semantic similarity measures and image entities are correlated using low-level and high-level image features. The proposed system also presents an integrated view of these entities and their relations in the form of a knowledge base using OWL. The system is tested for a collection of crime related articles from popular Indian online newspapers.

Widely known as the “Panama Papers,” the world’s largest whistleblower case to date consists of 11.5 million documents and involves a year-long effort by the International Consortium of Investigative Journalists to expose a global pattern of crime and corruption where millions of documents capture heads of state, criminals and celebrities using secret hideaways in tax havens. Involving the scrutiny by over 400 journalists worldwide, these documents reveal the offshore holdings of at least several hundred politicians and public officials, including the prime ministers of Iceland and Pakistan, the president of Ukraine, and the King of Saudi Arabia. More than 214,000 offshore entities appear in the leak, connected to people in more than 200 countries and territories.Since these disclosures became public, national security implications already include abrupt regime change, and probable future political instability. It appears likely that important revelations obtained from these data will continue to be forthcoming for years to come. Presented here is Part 1 of what may ultimately constitute numerous-installment coverage of this important inquiry into the illicit wealth derived from bribery, corruption, and tax evasion. This article proceeds as follows. First, disclosures regarding the treasure trove of documents from the Panama-based law firm, Mossack Fonseca are reviewed. Second, is a discussion of the impact and cost of bribery and corruption to the global community. Third, I define and briefly explore issues surrounding “tax evasion.” Fourth, the impact of social media and technological change on transparency is discussed. Next, a few thoughts about implications for future research are offered.

The Arab Uprisings represented a series of events unprecedented in the history of the Middle East: mass, popular and largely non-violent uprisings took place starting in December 2010 in Tunisia and reverberating throughout the region. These protests threatened – and in several cases resulted in the overthrow of – apparently stable autocratic regimes. The unprecedented nature and extensive domestic, regional and international impact of the Uprisings in and of itself merits attention, but coming hard on the heels of a global financial crisis and given the resonance of the Arab Uprisings with protest movements beyond the region, these Uprisings appear all the more significant beyond the region itself. The significance of the Uprisings is not just academic, however: the Middle East is one of the most frequently conflictual regions in the world, it is central to the global political economy – e.g. as a source of hydrocarbon fuels, and as a global logistical nexus – it is a source of and transit point for migratory flows towards Europe, and its autocracies have been supported as key allies by Western governments, both in Europe and North America. This project aims to generate new data and analyses of the Uprisings themselves, but is also sensitive to the policy implications of these analyses. The objective of the ArabTrans project is to contribute particularly to a better empirical understanding of the Uprisings and of the longer-term processes that lead to them and which they epitomise. To do this, the project will a) identify the principal approaches to transitions between political systems as they pertain to the Middle East generally and to the Arab Uprisings in particular; b) identify a series of political, economic, and social categories and variables based on these orthodox approaches; c) evaluate the available literature and existing data on the basis of these variables; and d) design a survey based on available data in order to facilitate the creation of a useful longitudinal database against which long-term trends and transformations might be identified. While the project will use existing data sets from public opinion surveys to look at long-time trends and transformations in public opinion, it will update and integrate these data by carrying out a new survey which will provide up to date information on public opinion in the MENA countries in 2014. This survey will use relevant questions that have been used in previous surveys to facilitate the longitudinal analysis as well as adding new questions to answer questions that arise from the literature review, particularly focusing on security, detailed questions on participation in the Uprisings and on EU-MENA relations, as well as additional questions on media, including social media use. These survey data will then be combined in a longitudinal database with non-survey quantitative data, enabling measurements of long-term trends and transformations

The pervasive, alluring, and uniquely powerful nature of social media has swept across many social boundaries; broken the traditional ways of communicating, giving a voice to the voiceless and rendering those powerless powerful; all with the click of a mouse, a “status update” or in other cases a “tweet.” This new trend of the use of social media by the religious community shows in many ways the profound effects of new media technologies in shaping culture, actions and behaviours; of which the church has become active participants in its use. However, what really is the agenda of the church in this regard? Are the effects of new media technologies reshaping their “soul winning agendas? This paper will discuss the aforementioned, with reference to the use of social media, specifically facebook, among Christian churches in Guyana.

Social media, sites where users can generate content and interact with each other, such as Facebook, Twitter and Blogger, have placed trademark holders for “brand” new challenges and opportunities. Trademark holders seem to have unwittingly signed a Faustian pact with social media sites. On the one hand they can reap the benefits of two-way contact with users who co-create value for the brand. On the other hand, trademark holders seem to have lost all control over their brand integrity. A fortiori, because of the interconnectedness of social media good and bad brand exposure can spread like wild fire. Current trademark law as such cannot offer all solutions. But not all is lost for trademark holders. Social media are basing their business models on advertising. Social media have the characteristics of walled gardens which have the potential to better cater to the needs of all stakeholders than would be possible in the outside world. This paper asserts that if a balanced and transparent system is implemented in regard to brand integrity it would improve business predictability for trademark holders and social media, and legal certainty for trademark holders, social media and users alike.

Background Handwashing has long been promoted to maintain health and in preventing disease transmission. One of the most valuable ways to convey messages related to handwashing is through visual display, such as video for educational purposes and to enhance learning. Social media is an important and popular way to disseminate messages to a wide audience. Methods In this cross-sectional, descriptive study, two hashtags, #WashYourHands and #SafeguardSplash were used to select the sample of 100 from available TikTok videos. In order to code each video, the same coding categories were used for both hashtags, including (1) wetting and rinsing hands (2) lathering soap (3) time used for scrubbing (4) drying hands (5) mentions COVID-19 (6) mentions using hand sanitizer instead of soap (7) mentions how germs spread (8) mentions key times to wash hands (9) and actual depiction of washing hands. Additional descriptive categories were coded as well. The observations recorded were tabulated and descriptive statistics were performed. Independent one-tailed t-tests (α = .05) were calculated to determine if a video's hashtag had a significant association with its garnered views, likes, and/or comments. Results In total, the 100-video sample received 1,990,834,567 views, 40,355,468 likes, and 173,422 comments. Despite the fact that each hashtag made up an equal proportion (50%) of the total sample, videos with #WashYourHands accounted for 93.3% of the total views. Coverage of the important steps involved in handwashing, such as drying hands, was minimal as was relevant background information. Conclusion The results indicate that while this opportunity is being realized to some degree, the majority of videos did not cover topics related important concepts of hand hygiene. Given the high engagement of younger audiences with TikTok, this could be a powerful mechanism for demonstrating and encouraging proper handwashing, especially in a population with low rates of handwashing.

The involvement of patients in nephrology clinical trials is limited despite their ability to prioritise research, help with study design, participation and implementation of results. The aim of this position paper is to review the need, challenges and assess the present situation of patient involvement; and describe the role of International Society of Nephrology in promoting patient involvement. Patient involvement across from priority setting through to implementation of the trial findings can ensure that the evidence generated aligns with their priorities, maximises recruitment and retention, as well as its impact on practice and policy. This has been demonstrated in UK, Australia, Canada and United States, however little is known about the involvement of patients in trials internationally. Barriers to patient involvement includes the patients’ lack of awareness of opportunities to participate, knowledge of clinical research, lack of time, ill health; and lack of initiative amongst researchers to provide opportunity. To assess patient involvement in clinical trials in kidney disease the International Society of Nephrology surveyed the members of the regional boards to which 177 members responded. The survey demonstrated the variability in patient involvement among different regions, highlighted the lack of nominated leads and formal mechanisms of patient involvement. Though members were keen to communicate with patient, social media was underutilised. The International Society of Nephrology will support patient involvement by developing tools and creating better awareness, to promote high quality clinical trials in Nephrology.

Objectives This article seeks to demonstrate the impact of distributing boxes of art resources and guided activities for vulnerable parents and infants to do together at home. Study design Designed in conjunction with the local arts centre and the psychology team at the University of Dundee, the art boxes were a response to planned face-to-face art interventions with families being cancelled due to COVID-19 restrictions. The aim of the art boxes is to encourage parents to make art together with their infants, fostering connection through playful, creative shared experiences. This research is currently being expanded to reach out to new families through referrals from health visitors, family nurses, and charity partners. Methods Data is being collected on how the art boxes are experienced by families using a mixed-methods approach. Families complete feedback cards (online, or using the stamped addressed card included in the box) rating their experience on quantitative scales and providing open comments. Visual data are gathered through parents sharing images with us on social media. An initial sample of 10 participants has been interviewed using semistructured interviews, allowing more in-depth qualitative understanding of their experiences. These preliminary findings are discussed here. Results The thematic analysis of initial interviews provided a rich picture of the disconnection families experienced during lockdown, why art boxes may be beneficial to parental well-being, and the mechanisms by which the boxes may help to develop connections for the parent and infant together. Conclusions Preliminary findings show parents reporting feeling more confident and undertaking new activities which they plan to continue. This was of particular importance during lockdown where parents report opportunities for different experiences being more limited. Parent’s describe positive playful interactions and reported improvements to their own well-being from doing creative activities together with their child. Analysis of these initial interviews gives a framework of barriers and supports to connection which highlights how art boxes can facilitate connectedness between dyads with the potential to strengthen attachments., Highlights • The Art at the Start project provided an art-based intervention for parents and young children at home. • We undertook thematic analysis of parent interviews about their experiences. • This found themes of ways that art making supported connectedness. • We found evidence of art making improving well-being and supporting connections.

The American Antitrust Institute (AAI) has released the White Paper, Update on Digital Technology: The Failure of Merger Enforcement and Need for Reform. The new White Paper updates and expands on analysis AAI originally released in July 2019. The widely cited 2019 AAI White Paper, The Record of Weak U.S. Merger Enforcement in Digital Technology, was the subject of AAI testimony before the Senate Judiciary Committee and drew attention to the acquisitive history of the five largest multinational online service or computer hardware or software companies: Amazon, Apple, Facebook, Google, and Microsoft (“Big Tech”). It also unpacked the history of merger enforcement under Section 7 of the Clayton Act in a major segment of the digital technology sector. The White Paper concluded that, as compared to enforcement across all sectors, the rate of merger challenges in digital technology is exceptionally low. Since then, much has happened in the digital technology sector. Big Tech has solidified its hold on the top-most slots, by market value, in the Fortune 500. Federal and state monopolization cases have been filed against Google and Facebook. Among other things, the Facebook complaints allege that acquisitions of small rivals, such as social media firms Instagram (2012) and WhatsApp (2014), were a strategy to snuff out potential competition to maintain a monopoly in personal social networking services. The public policy debate over the dominance of Big Tech has also generated numerous proposals to remedy competitive and consumer harm, including breakups and digital market regulation. A 2020 House Judiciary Committee report examined competitive issues raised by the platforms that are at the core of many of the large digital ecosystems. Moreover, the digital ecosystems have been the subject of ongoing economic, business, and policy research, which has advanced the state of thinking over potential policy solutions to the problems they raise. Results of AAI’s updated analysis indicate that expansion by acquisition continues to be a leading method by which the large digital ecosystems grow. Enforcers can expect to see further growth that, when juxtaposed with persistent, weak merger enforcement in the sector, will likely exacerbate competition problems. Indeed, stronger merger enforcement over the last two decades would have mitigated the monopolization concerns that AAI sees now. As it stands, however, Section 2 of the Sherman Act is virtually the only antitrust tool left to combat dominance in the digital technology sector. This White Paper turns first to updating data on acquisitions by Big Tech through 2020 and merger enforcement statistics through the latest available reporting year, 2019. It then examines the implications of Big Tech’s likely trajectory of further expansion through acquisition and growth in critical cloud infrastructure capability. It closes with an analysis of reforms necessary to revitalize merger enforcement in digital technology.

Based on complex adaptive system theory and information theory for investigating heterogeneous situations, this paper develops an outlier knowledge management framework based on three aspects—dimension, object, and situation—for dealing with extreme public health events. In the context of the COVID-19 pandemic, we apply advanced natural language processing (NLP) technology to conduct data mining and feature extraction on the microblog data from the Wuhan area and the imported case province (Henan Province) during the high and median operating periods of the epidemic. Our experiment indicates that the semantic and sentiment vocabulary of words, the sentiment curve, and the portrait of patients seeking help were all heterogeneous in the context of COVID-19. We extract and acquire the outlier knowledge of COVID-19 and incorporate it into the outlier knowledge base of extreme public health events for knowledge sharing and transformation. The knowledge base serves as a think tank for public opinion guidance and platform suggestions for dealing with extreme public health events. This paper provides novel ideas and methods for outlier knowledge management in healthcare contexts., Highlights • Develop an outlier knowledge management framework for dealing with extreme public health events. • Conduct data mining and feature extraction on the microblogs from Wuhan and nearby areas. • Analyze the semantic and sentiment vocabulary, the sentiment curve, and the portraits of patients. • Acquire outlier knowledge of COVID-19 and incorporate it into the outlier knowledge base.

Highlights • The COVID-19 pandemic had significant mental health impacts on the population of Kuwait. • Unemployment, uncertainty, distress, increasing deaths and lockdown measures contribute to the burden. • From our experience risk factors include; female, smoker, past psychiatric history, increased social media use. • Availability of psychological support and mental health awareness reduces the burden., Background In February 2020 the first cases of COVID-19 were identified in Kuwait. Inevitably as many countries worldwide, the general public were negatively affected by the pandemic. Unemployment, uncertainty, distress, increasing deaths, lockdown measures all of which are potential burdens on mental health. Aim To assess the impact of COVID19 outbreak on mental health in Kuwait, and to explore the potential influencing risk factors. Methods We conducted an online questionnaire-based study in Kuwait between 25th May 2020 to 30th May 2020. Questions were based on demographics, lifestyle during outbreak, depression and anxiety assessment. Total PHQ9 and GAD7 scores were calculated for each responder. Results We had 4132 responders. Most were females (69.31%), married (59.37%), between the age of 21-30 (23.84%) and non-smokers (81.46%). Only (7.96%) had a positive past psychiatric history, (32.04%) had a past history of a chronic medical disease. During the outbreak most of the responders lost their jobs (39.21%) and only (12.83%) were attending work regularly, only (6.82%) worked in the healthcare sector. 59.27% report increased social media use compared to before the lockdown. When asked about their daily time spent following COVID19-related news, most (37.8%) spend more than 2 hours and (7.74%) spend more than 4 hours. The overall prevalence of depressive symptoms was (30.13%) and the prevalence of anxiety symptoms was (25.28%). Limitations In the cross-sectional nature of the study. Conclusion The COVID-19 pandemic caused a burden on mental health. Psychological support and mental health awareness should be implemented and made accessible to all individuals during pandemics.

Background: Evidence suggests social media use is associated with mental health in young people but underlying processes are not well understood. This paper i) assesses whether social media use is associated with adolescents' depressive symptoms, and ii) investigates multiple potential explanatory pathways via online harassment, sleep, self-esteem and body image. Methods: We used population based data from the UK Millennium Cohort Study on 10,904 14 year olds. Multivariate regression and path models were used to examine associations between social media use and depressive symptoms. Findings: The magnitude of association between social media use and depressive symptoms was larger for girls than for boys. Compared with 1–3 h of daily use: 3 to

This report is the eighth in an annual series of publications, dating back to 2012, designed to share the latest stories, trends and research in social media usage from across the Middle East and North Africa (MENA). Using a wide variety of academic, industry and media sources, this White Paper identifies important insights from social media’s development over the previous year. Of particular note in 2019 is the continued, growing, importance of social media in the lives of Arab Youth, outside of Saudi Arabia and Turkey the declining usage of Twitter (once the poster child social network for the Arab Spring,) as well as greater scrutiny of social media usage by platform owners and governments alike. Last year’s report highlighted the increasing weaponization of social networks, a trend which continued in 2019. Facebook, Twitter and Telegram each closed hundreds of accounts due to inappropriate use by state sponsored actors and terrorist groups. Social networks were also the target of governments across MENA, in the midst of protests in many countries throughout the region. Meanwhile, the importance of social video and visually-led social networks, continued to grow from strength to strength. Snapchat introduced new advertising formats to the region and other exclusive functionality, Google highlighted the importance of YouTube in supporting parents and parenting, and in major markets such as Egypt, Saudi Arabia and the UAE, Twitter has emerged as a leading platform for online video consumption. The year ahead is likely to result in a continuation of many of the trends outlined in this report, as social media becomes increasingly engrained across the lives of businesses, governments and residents across the MENA region.

E-cigarettes were initially introduced as a less harmful alternative to combustible cigarettes, but marketing efforts may now be exceeding these claims by associating e-cigarettes with words related to healthy foods. These associations could mislead people to assume vaping is a healthy practice. Tweets from January to March 2017 were obtained from the Twitter Streaming Application Programming Interface (API) to assess content about vaping linked to healthy food words. Tweets were classified into one of nine categories along with their source (marketer vs. non-marketer). We content analyzed original English language public postings on Twitter that included vaping-related keywords and at least one of eight co-occurring healthy food-related labels (e.g., ‘natural,’ ‘vitamin,’ ‘vegan,’ and ‘organic’) (N = 1205). Chi-square analyses compared themes by message source. Findings suggest vaping is being marketed in ways that could paradoxically lead consumers to believe that e-cigarettes are health-enhancing. We found more tweets representing vaping as health-enhancing (9%) than referring to it as a smoking-cessation device (1%). The largest category of tweets referred to vaping as harmless (28%) and therefore compatible with a healthy lifestyle. Tweets presenting vaping as harmless or with a sensation theme were more likely to be authored by marketers than by non-marketers. Food and drug regulation needs to be more vigilant to prevent misleading advertising from e-cigarette marketers., Highlights • 9× more ‘health-enhancing’ tweets than ‘quit smoking’ • 9% of sampled tweets said vaping is health-enhancing. • 27% of healthy-food tweets said vaping is harmless. • Marketers wrote 64% of ‘health-enhancing’ vaping tweets. • About one fourth of sampled tweets were about flavors.

Highlights • We compared a 10% vs. 50% reduction in social media screen time in a RCT. • The intervention had no effect on multiple indicators of attention and wellbeing. • Self-control, impulsivity and FoMO did not moderate the relationships. • Participants reported improved attention, but behavioral attention did not improve. • Overall, a more severe screen time reduction intervention does not appear more beneficial., Introduction Screen time apps that allow smartphone users to manage their screen time are assumed to combat negative effects of smartphone use. This study explores whether a social media restriction, implemented via screen time apps, has a positive effect on emotional well-being and sustained attention performance. Methods A randomized controlled trial (N = 76) was performed, exploring whether a week-long 50% reduction in time spent on mobile Facebook, Instagram, Snapchat and YouTube is beneficial to attentional performance and well-being as compared to a 10% reduction. Results Unexpectedly, several participants in the control group pro-actively reduced their screen time significantly beyond the intended 10%, dismantling our intended screen time manipulation. Hence, we analyzed both the effect of the original manipulation (i.e. treatment-as-intended), and the effect of participants’ relative reduction in screen time irrespective of their condition (i.e. treatment-as-is). Neither analyses revealed an effect on the outcome measures. We also found no support for a moderating role of self-control, impulsivity or Fear of Missing Out. Interestingly, across all participants behavioral performance on sustained attention tasks remained stable over time, while perceived attentional performance improved. Participants also self-reported a decrease in negative emotions, but no increase in positive emotions. Conclusion We discuss the implications of our findings in light of recent debates about the impact of screen time and formulate suggestions for future research based on important limitations of the current study, revolving among others around appropriate control groups as well as the combined use of both subjective and objective (i.e., behavioral) measures.

This short paper reviews Hannibal Travis' "Copyright Class Struggle - Creative Economies in a Social Media Age, Cambridge University Press, 2018".

Using an international sample of 2,113 initial coin offerings (ICOs), we explore the role of disclosure and information intermediaries in the unregulated crypto-tokens market. First, we document substantial cross-sectional variation in the voluntary disclosure practices of ventures seeking to raise capital through ICOs, such as the extent of information released in a prospectus-type document called a white paper; releasing the technical source code; and communicating through social media platforms. Second, we find that, even with limited disclosure verifiability, ventures with higher levels of disclosure have a greater ability to raise capital. Finally, we find that this association is stronger in the presence of mechanisms that lend credibility to ventures’ voluntary disclosures, such as internal governance practices or external scrutiny from information intermediaries. Overall, our results suggest that voluntary disclosure and information intermediaries facilitate the functioning of ICOs as an alternative capital market.

This report is the sixth in a series of annual reports designed to highlight key developments and data related to usage of social media in the Middle East and North Africa. As in previous reports, this White Paper captures insights from a wide variety of academic, industry and media sources, distilling the key lessons from the past year. Social Media adoption, and usage, around the world continues to rapidly evolve; and the Middle East is no exception. This 2017 research and industry round-up highlights the increasing prominence of visually led social media in the region, and the ongoing popularity of Facebook’s different products.

Highlights • This study showed a prevalence measure of addicted gamers as 1.2 percent. • Male gender was associated to problematic and addictive gaming. • Young age was associated with both engaged-, problem- and addictive gaming. • Hours spent on chatting was associated with both engaged-, problem- and addictive gaming. • Loneliness was associated with both engaged-, problem- and addictive gaming., Introduction Gaming disorder was included in the 11th revision of the International Classification of Diseases (ICD 11) and the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included Internet Gaming Disorder as a tentative diagnosis. Most scholars agree upon the potential risk for pathological use of video games. The primary aim of this study was to investigate the prevalence of engaged gamers, problem gamers and addicted gamers. The secondary aim was to describe these groups in terms of gender, age, social satisfaction, psychological wellbeing and hours spent chatting on internet/social media. Methods We used survey-based data for this population-based research. The data was collected online in two different settings in 2017. In total 2075 participants were included. Results 4.5 percent met the criteria for highly engaged gaming, 5.3 percent were shown to be problem gamers and 1.2 percent met the cut off for game addiction. Young age, hours chatting on internet/social media, experiencing loneliness and considering seeking treatment for psychological distress were associated with both engaged, problematic and addictive gaming. Male gender was associated to problematic and addictive gaming. Hours spent chatting showed a greater correlation to problem/addictive gaming than to engaged gaming. Conclusion The results of this study indicate that both highly engaged gamers, problem gamers and addicted gamers all experience loneliness and psychological distress to a greater extent than the remaining study participants. This adds to the knowledge of prevalence and features of gaming disorder. Additionally, preferably longitudinal research is needed in order to understand causality.

This study examines a case in which activists used a corporation's social media page to disseminate activist campaign messages. Specifically, we examine how a blogger–activist took advantage of an online hoax regarding a warning label for Kraft Macaroni and Cheese to spur others into hijacking Kraft's Facebook page. While the hoax was quickly exposed, the reputation damage was done and within 6 months Kraft announced it was changing the ingredients in some products. This study offers several implications for online activists and public relations researchers and practitioners by (1) providing an example of how traditional activist strategies have adapted for the online environment; (2) presenting hoax as a viable, albeit potentially unethical, strategy to motivate action; (3) showing the impact of social media hijacking and dismissing the notion that “slacktivism” cannot lead to change; (4) encouraging further research on collaborative relationships between activist groups; and 5) outlining the benefits of more proactive issue management strategies.

New Yorkers are now safer in the city than they have been in years. Yet tensions between police officers and the communities in which they work have continued to mount in New York, as in other cities across the country. Just this past summer, racial violence erupted in Milwaukee and Baton Rouge in response to the fatal shooting of Philando Castile and Alton Sterling. Milwaukee joined other cities like Baltimore and Ferguson, Mo., in which police killings have been seen as brutal evidence of the disrespect that many African Americans say the police show them. The challenge facing the NYPD today is to maintain safe streets while ushering in a new era of mutual respect between officers and local communities. At this early stage of digital technology adoption, the NYPD’s attempt under Commr. William Bratton (2014-2016) to change the culture of policing by enriching communications between police and neighborhoods holds lessons for public agencies across the U.S. during a period of intense volatility. This white paper explores NYPD’s adoption of Twitter and an ideation platform called IdeaScale that was aimed at allowing community members to nominate “quality of life” issues for resolution by the police. It examines the department's pivot to Facebook as an interactive communications platform following its experience with IdeaScale. It connects these initiatives to the NYPD’s overall push for Neighborhood Coordination Officers throughout the city. Finally, it pulls together information about NYPD’s revisions to its training and recruitment programs and the department’s ongoing efforts to upgrade its basic digital assets, from precinct Internet access to smartphones. These programs, all made possible by Commr. Bratton’s strong leadership, were designed to create a virtuous cycle: The NYPD’s social media, neighborhood policing, and new recruiting and training programs aimed to increase mutual respect by helping officers understand and enhance their responsibility to serve and protect New York City communities — and help community members see police officers as human beings. Stronger community relations may, in turn, support crime prevention. Shifting from a confrontational to a collaborative approach may encourage community members to come forward when they learn about crime. And all of these steps are designed to lead policing away from an exclusive focus on crime reduction and towards a balanced strategy of crime prevention and community outreach — an effort, in Commr. Bratton’s words, to move from a “warrior” to a “guardian” policing mindset.

This white paper (adapted from a blog post at the EdTechResearcher website) provides a summary of the first scholarly publication from Distributed Collaborative Learning Communities project: “The State of Wiki Usage in U.S. K-12 Schools: Leveraging Web 2.0 Data Warehouses to Assess Quality and Equality in U.S. K-12 Schools.” The article was published in the February 2012 issue of Educational Researcher, the flagship journal of the American Educational Research Association. The article can be found through this direct link or at this landing page. I’m very grateful to the Hewlett Foundation’s Open Educational Resources initiative for financial support, and to my co-authors Richard Murnane and John Willett.The article is written for a general audience of education researchers, and while I think it’s highly readable (so far as scholarly articles go), many folks may prefer a simpler version of the article. This white paper, therefore, is particularly targeted at classroom teachers and other school educators to share a bit about our findings and suggestions for using social media in classrooms. First, I explain what we did, and then I give some advice for wiki using educators.

Recently, Social Media (SM)’s adoption as educational instruments in Higher Education (HE) has been gaining popularity among researchers and practitioners. Nonetheless it has been adopted to support various learning approaches such as Cooperative Learning (CL). Despite the growing research in this field, few studies have proposed a comprehensive SM integration framework as well as empirical studies to evaluate its effectiveness. This paper examines how SM is being used as a pedagogical tool in HE and identifies major factors that drives SM’s inclusion in HE classrooms. In addition, the paper investigates the effectiveness of a previously proposed integration framework which was developed to promote CL using a popular SM platform, LinkedIn. A survey was administered to collect data from students in different subjects at a university in Australia. Structural Equation Modelling (SEM) was adopted for data analysis using IBM’s SPSS26 and AMOS26. One of the notable results of this study is the significant positive relation found between the use of the adopted integration framework and CL, SM challenges’ mitigation, students’ intention to use SM and their learning process. The findings of this study have important implications for practice and pave the way for future empirical studies.

Affect detection from text has captured the attention of researchers recently. This is due to the rapid use of social media sites (e.g. Twitter, Facebook), which allows users to express their feelings, emotions, and thoughts in textual format. Analyzing emotion-rich textual data of social networks has many real-life applications. The context of an emotional text can be measured by analyzing certain features of this rich source of emotional information. Classifying text into emotional labels/intensities is considered a difficult problem. This paper resolves one of the state-of-the-art NLP research emotion and intensity detection tasks using Deep Learning and ensemble implementations. In this paper, we developed several innovative approaches; (a) bidirectional GRU_CNN (BiGRU_CNN), (b) conventional neural networks (CNN), and (c) XGBoost regressor (XGB). The ensemble of BiGRU_CNN, CNN, and XGB is used to solve an emotion intensity (EI-reg) task of the SemEval-2018 Task1 (Affect in Tweets). Our proposed ensemble approach was evaluated using a reference dataset of the SemEval-2018 Task1. Results show that our approach is well above the baseline for this task. It also achieved a Pearson of (69.2%), with an enhancement of 0.7% in comparison with previous best performing models.

The tremendous growth of event dissemination over social networks makes it very challenging to accurately discover and track exciting events, as well as their evolution and scope over space and time. People have migrated to social platforms and messaging apps, which represent an opportunity to create a more accurate prediction of social developments by translating event related streams to meaningful insights. However, the huge spread of ‘noise’ from unverified social media sources makes it difficult to accurately detect and track events. Over the last decade, multiple surveys on event detection from social media have been presented, with the aim of highlighting the different NLP, data management and machine learning techniques used to discover specific types of events, such as social gatherings, natural disasters, and emergencies, among others. However, these surveys focus only on a few dimensions of event detection, such as emphasizing on knowledge discovery form single modality or single social media platform or applied only to one specific language. In this survey paper, we introduce multiple perspectives for event detection in the big social data era. This survey paper thoroughly investigates and summarizes the significant progress in social event detection and visualization techniques, by emphasizing crucial challenges ranging from the management, fusion, and mining of big social data, to the applicability of these methods to different platforms, multiple languages and dialects rather than a single language, and with multiple modalities. The survey also focuses on advanced features required for event extraction, such as spatial and temporal scopes, location inference from multi-modal data (i.e., text or image), and semantic analysis. Application-oriented challenges and opportunities are also discussed. Finally, quantitative and qualitative experimental procedures and results to illustrate the effectiveness and gaps in existing works are presented.

Recently, the social media podium used to share and post patient medical content, which significantly lead to mining medical content for pharmacovigilance, drug repositioning, and Healthcare sector. Paramedical advertisers extract trusted health information from the social media platform and correlate health care information with the user profile for recommending proper treatment. The mining of the patient's personal and medical information on social media makes the patient aware of the recent drug revolution. For predicting computational medical services, there is a need to Develop a centralized Social media-based pharmacovigilance activities virtual podium that identify drug and ADR associated with it. Build an informational community of homogenous E-patient over the virtual platform for building informational and emotional support more efficiently. In this paper, a comprehensive overview of the recommendation system and possible research gap associated with drug repository and ADR are presented based on recent research. Furthermore, this paper present clinical post pre-processing, clinical entity recognition, tweet pooling and expert rating framework to classify Disease-Drug-ADR intersection for recommending drug and ADR. Simultaneously this framework present comparative analysis of benchmark classifier to trained and label corpus of tweets for drug repositioning and ADR automatically.

In today's day and age, there are billions of volumes of textual content being generated everywhere. In-apps messages like WhatsApp, Telegram, social media sites like Facebook, Instagram, news publishing sites, google searches and many other sources. All these sources are constantly generating huge volumes of text data every second. And because of these huge volumes of text data NLP becomes a vital resource in understanding the textual content. In this paper, the main focus is on the popular NLP task of Sentiment analysis. Sentiment analysis is contextual mining of text which identifies and extracts subjective information in textual data. sentiment analysis proves to be an incredible asset for users to extract essential information and assists organizations with understanding the social sentiment of their brand, product or service while monitoring online conversations. This paper investigates the different approaches and classification models used in the task of sentiment analysis.

Online social media networks are gaining attention worldwide with an increasing number of people relying on them to connect, communicate and share their daily pertinent event-related information. Event detection is now increasingly leveraging online social networks for highlighting events happening around the world via the Internet of People. In this paper, a novel Event Detection model based on Scoring and Word Embedding (ED-SWE) is proposed for discovering key events from a large volume of data streams of tweets and for generating an event summary using key words and top-k tweets. The proposed ED-SWE model can distill high-quality tweets, reduce the negative impact of the advent of spam, and identify latent events in the data streams automatically. Moreover, a word embedding algorithm is used to learn a real-valued vector representation for a predefined fixed-sized vocabulary from a corpus of Twitter data. In order to further improve the performance of the Expectation-Maximization (EM) iteration algorithm, a novel initialization method based on the authority values of the tweets is also proposed in this paper to detect live events efficiently and precisely. Finally, a novel automatic identification method based on the cosine measure is used to automatically evaluate whether a given topic can form a live event. Experiments conducted on a real-world dataset to demonstrate that the ED-SWE model exhibits better efficiency and accuracy than several state-of-art event detection models.

Many B2B firms have widely accepted AI-based chatbots to provide human-like service interaction at different customer touchpoints in recent years. One of the objectives behind introducing this technology is to provide an enhanced, live channel Customer Experience (CX) all round the clock. Researchers have focused on delivering the CX by improvising the chatbot's internal algorithm, giving limited attention to CX theories from management literature, which leaves a gap. With the proposed paper, we have investigated the influencing factors of AI-based chatbots from the lens of CX theories for B2B firms. In this paper, a model for organizing CX has been proposed using the diffusion of innovation theory, trust commitment theory, information systems success model, and Hoffman & Novak's flow model for the computer-mediated environment and verified using the social media data. The methodology used for this study is the social media analytics-based content analysis method (sentiment analysis, hierarchical clustering, topic modeling) for data preparation, followed by lasso and ridge regression for model verification. The results suggest that CX in B2B enterprises using chatbots is influenced by these bots' overall system design, customers' ability to use technology, and customer trust towards brand and system.

Social media influencers (SMIs) are increasingly involving in influencer marketing to promote products. However, there are both opportunities and issues with influencer marketing. SMIs’ narrative strategies can be of great value as high-quality eWOM content is vital to maintain influencer marketing effectiveness. This paper adopts the stimulus-organism-response (S-O-R) framework to explore the value of SMIs’ narrative strategies to overcome potential influencer marketing issues within the context of China’s luxury market. A qualitative approach is applied to explore Chinese consumer perceptions toward capabilities of three SMIs’ narrative strategies (brand attribute evaluation, brand love inspiration, self-identity construction) to deal with the issues of cultural barriers, commercial–personal tension, and sponsorship disclosure in SMIs’ eWOM. Based on the research findings, this paper develops a conceptual model to illustrate how SMIs’ narrative strategies benefit the cultivation of influencer marketing on social media.

Terrorist attacks, and other short-scale emergencies such as active shooting events, have the potential to cause major loss of life they occur in passenger transportation terminals. Regulations often require airport authorities to be prepared for these events, but there is a lack of empirical data available to enhance response plans. Recently, there has been significant interest on how user-generated content available on social media platforms could aid with management and planning in response to emergencies. However, little of this has focused on active shooting events in particular. This paper uses a case study approach to analyse the content of social media posts to evaluate their potential to aid with situational awareness during the response phase of short-scale emergency events. Alongside a literature review conducted into this topic, this paper details the results of the analysis of 131,600 Twitter posts related to the case study active shooting event – which occurred in 2017 at Fort-Lauderdale Hollywood airport in Florida. Qualitative content analysis, and two machine learning algorithms – a Support Vector Machine, and a Latent Dirichlet Allocation model were used to categorise the tweets produced in relation to this event. Results indicate that the majority of tweets produced either simply stated that the event had occurred, or were emotional in nature, expressing worry or prayers for victims. Very few posts detailing behavioural responses of individuals involved in the event were identified. Thus, it is suggested that social media data would not be of particular use to improving situational awareness during response to short-scale emergency events in transportation terminals. Instead, social media may be of more use for information dissemination or conversations and coordination purposes during the preparation, recovery or mitigation phases of an emergency event.

New user recommendation is a big challenge for social networks site like reddit, where user profile is not so much rich. The aim of this paper is to enhance recommendation process that reddit can used for its users. We know that twitter and Facebook generate rich user information for social media behavior analysis and research. reddit recommendation system usually implement generic recommendation for its users in order to recommend subreddit, other side of coin, Like LinkedIn, amazon have very specialized user and item recommendation system based on user detail and create effective user profile for future reference. In this work fusion twitter and Facebook dataset user profile building by using tweets and post posted on Facebook by authentic unique user, and after that we extract user profile feature and parallelly perform subreddit listing for specific user feature generated by profile building. As per the reddit rank it is the 5th most visited site of USA and in world it holds 13th rank of most visited site. Twitter has 330 million active users with rich user profile like user demography. In this paper we analyze user timeline and identify user interest using machine learning and extract keywords using TF-IDF. Given the output with this machine learning used as input for a web based reddit subreddit listing application.

The paper focuses on the use of social media in the process of acquisition of the second language (L2) or foreign language learning (FLL), namely, English in university students. Recently, we have seen a dramatic change in favour of distance learning due to the COVID-19 pandemics, therefore, it could be useful to analyse the impact of social media in FLL as they have been used much more now. It is a study summarizing the most important findings of the most recent research into the impact of social media on L2 acquisition from the psycholinguistic perspective. The paper analyses data from research papers as they appear in Scopus and Web of Science databases in the past ten years (i.e. 2010-2020). The purpose of the study is to describe the current research findings, to analyse their importance, to compare the most important data, and to look for further development of the psycholinguistics of L2. Its primary intention is to look into the acquisition of L2, particularly English as a second language (ESL) in the younger generation, i.e., Generation Z of current university students. It also attempts to highlight both the advantages and disadvantages of using social media in L2 acquisition and therefore to highlight future strategies regarding FLL in university education. The current research in this area provides us with overtly optimistic results in FLL with the assistance of social media, however, the paper claims that the situation of utilizing social media in FLL needs further investigation and analysis, mainly from the psycholinguistic point of view. The current COVID-19 situation makes us aware that the impact of social media will increase due to social distancing. © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.

Drawing on recent debates around food, space and digital media, this paper introduces and develops the concepts of the digital foodscape and ‘good’ food grammars. Through a quantitative and qualitative analysis of digital platforms, discourses and personas, we investigate the ways a key set of digital food influencers (DFIs) construct, curate and share the meanings of good food. We first explore who these influencers are, describe what platforms they inhabit, how the variable social media affordances work through these platforms and the notions of good food they construct. We then focus specifically on DFIs’ communicative practices on Twitter to analyse the core discourses DFIs produce and those that are taken up by audiences through re-tweets and likes as well as the re-tweeted tweets of DFIs. Overall, our findings suggest that first, good food grammars are being constructed by rule setters beyond the already well-established food personalities and celebrity chefs of the UK’s foodscape. Yet, these grammars also re-inscribe a form of white, hetero-normative middle- and upper- class privilege that produces particular grammars of good food. Second, different social media and digital platforms provide space for diverse good food grammars given their variable affordances. Twitter, in particular, is the place where the grammars of DFIs take on non-food themes such as self-empowerment, inspiration, charity campaigning and awareness raising. Third, the notions of good food in DFI grammars revolve around a range of constructions, with the most elevated related to ‘clean’ eating and/or ‘clean’ lifestyles that combined healthy, ‘free from’ diets with fitness regimes and expand DFI grammars – and ultimately their brands – into a more holistic lifestyle brand. This paper’s initial empirical and conceptual foray into digital foodscapes and DFIs opens up space for further research on food and digital media within Geography and beyond.

Smart Cities evolve into complex and pervasive urban environments with a citizens' mandate to meet sustainable development goals. Repositioning democratic values of citizens' choices in these complex ecosystems has turned out to be imperative in an era of social media filter bubbles, fake news and opportunities for manipulating electoral results with such means. This paper introduces a new paradigm of augmented democracy that promises actively engaging citizens in a more informed decision-making augmented into public urban space. The proposed concept is inspired by a digital revive of the Ancient Agora of Athens, an arena of public discourse, a Polis where citizens assemble to actively deliberate and collectively decide about public matters. The core contribution of the proposed paradigm is the concept of proving witness presence: making decision-making subject of providing secure evidence and testifying for choices made in the physical space. This paper shows how the challenge of proving witness presence can be tackled with blockchain consensus to empower citizens' trust and overcome security vulnerabilities of GPS localization. Moreover, a novel platform for collective decision-making and crowd-sensing in urban space is introduced: Smart Agora. It is shown how real-time collective measurements over citizens' choices can be made in a fully decentralized and privacy-preserving way. Witness presence is tested by deploying a decentralized system for crowd-sensing the sustainable use of transport means. Furthermore, witness presence of cycling risk is validated using official accident data from public authorities, which are compared against wisdom of the crowd. The paramount role of dynamic consensus, self-governance and ethically aligned artificial intelligence in the augmented democracy paradigm is outlined.

This paper aims to explore the importance of SM in fostering employee wellbeing and promoting through this relationship employee brand ambassadorship in new innovative lines. In this paper, we have proposed a conceptual framework on the role of SM usage to advance the theoretical understanding of SM usage and employee wellbeing, and employee brand advocacy. In doing so, we have framed a model embracing the effect of SM usage on employee wellbeing and employee brand advocacy, and how employee brand advocacy can act as vital communicational activity with various stakeholders of the organization. This study contributes in the literature, as the ending point of this paper is the theoretical formulation of a new relationship between SM employee usage with employee wellbeing and employee advocacy. This paper is proposing a model embracing the effect of SM usage on employee wellbeing and advocacy and, set up the boundaries for future empirical work.

Creating effective business-to-business (B2B) communications is an increasingly complex challenge for marketing managers. It requires a theoretical understanding of a number of puzzling, interacting components of an advertising stimulus. However, few academicians have pursued the goal of integrating and modeling how the B2B advertising process should be conceptualized. Gilliland and Johnston (1997) provided the first comprehensive model of the process, but B2B advertising has changed dramatically since this paper and demands an update to capture the new dimensions of the phenomenon. Using a systematic literature review to summarize recent trends, this paper incorporates the key changes in B2B advertising over the last 20 years. In particular, the authors explore a revised model of B2B effects, including (1) social media, (2) creativity and emotional appeals, (3) national culture, (4) brand equity and credibility, (5) ad experience social context, and (6) competing messages.

Prepositioning of assets and supplies prior to a disaster strike accelerates the response activities as it reduces the supply chain burden associated with humanitarian relief items. Unlike prior survey papers on pre-disaster and post-disaster humanitarian logistics, our paper has a specific focus on prepositioning of assets and supplies in the domain of natural disasters. The first aim of our paper is to review the main Operations Research and Management Science (OR/MS) journal papers published between 2000 and 2018 on this topic. We have statistically analyzed these papers based on contributions in different journals, number of papers per year, and type of disaster. We have also categorized the papers based on their decision variables into three categories: Allocation papers (“A”), Location papers (“L”), and Location-Allocation papers (“LA”). After that, we have assessed our current literature based on some of the methodological issues in Humanitarian Operations that gathered by Kovacs and Moshtari (2018). The second aim of our paper is research gap identification. Our key findings in this domain are that there is a lack of papers that: consider demand-side costs in their proposed model objectives; deal with uncertainty in funding, budget, asset and supply quantities, and infrastructure; considering prepositioning as a risk mitigation strategy; take reliability into account for reducing the risk of loss; consider prepositioning of medical staff and emergency crew; discuss the best time to start prepositioning of supplies and assets in confronting a foreseen disaster; use social media to better prepare for upcoming disasters.

The strategic use of Social Media can leverage innovation, relationships with customers, and the entrepreneurial orientation of the firm, as it provides useful knowledge to find new opportunities for innovation. Despite the relevance of this phenomenon to current hyper-competitive environments, empirical research on the topic remains scarce. To advance knowledge of this issue, the main purpose of the paper is to examine how Social Media use impacts the different dimensions of Corporate Entrepreneurship. Building on a sample of 201 technological firms, findings confirm that the use of Social Media tools impacted all dimensions of Corporate Entrepreneurship and enhanced firm performance. This paper contributes to the literature by empirically confirming how Social Media use helps to create business value. The study results also have important implications for managers, as they show the pathway managers must follow to harness the benefits of Social Media use to become more entrepreneurial.

Information systems research provides increasing evidence that women and men differ in their use of information technology. However, research has not sufficiently explained why these differences exist. Using the theory of reasoned action and social role theory, this paper investigates gender differences in people’s decisions about information sharing in the context of social networking sites (SNSs). We developed a comparative model of the information-sharing decision process across genders and theoretically explained why these differences exist. Data was collected from an online survey taken by American SNS users. We found that privacy risks, social ties, and commitment were more important in the formation of attitudes toward information sharing for women than men. Gender significantly moderates the relationship between people’s perceptions of information sharing and their intention to share information. This paper provides an enhanced understanding of gender differences in people’s decisions about sharing information on SNSs. It advances gender differences research into the use of newly emerged information technology and provides researchers insightful views of the role that gender plays in the social media era. Being aware of the research findings, practitioners may better engage their targeted stakeholders on SNSs and collect more useful information for business purposes.

The rise of social media has led to changes in how entrepreneurs carry out their day-to-day activities. Studies on social media and entrepreneurship are relatively new and fragmented in their focus, however there is increasing interest from academia and practitioners for further research and investigation within this area. This study systematically reviews research carried out in the domain of social media and entrepreneurship. A total of 160 papers, published between 2002 and 2018 were synthesised to identify critical theories and research methods used in the domain. Based on the extent review, an integrative framework was developed to identify relationships amongst elucidated constructs. While most papers investigated the factors that drive social media adoption and use by entrepreneurs, it was found that the use of social media by entrepreneurs had transcended marketing and it is now used in business networking, information search and crowdfunding for their business. This has led to significant impact with improved firm performance and innovation enhancement being the essential outcomes. The literature review and framework further understanding of social media and entrepreneurship research, providing a useful basis for future studies and informs practice in this area.

Social media sites like Twitter, Facebook, being user-friendly and a free source, provide opportunities to people to air their voice. People, irrespective of the age group, use these sites to share every moment of their life making these sites flooded with data. Apart from these commendable features, these sites have down side as well. Due to lack of restrictions set by these sites for its users to express their views as they like, anybody can make adverse and unrealistic comments in abusive language against anybody with an ulterior motive to tarnish one’s image and status in the society. So it became a huge responsibility for the Government and these sites to identify this hate content before it disseminates to mass. Automatic hate speech detection faces quite a lot of challenges due to the non-standard variations in spelling and grammar. Especially for a country like India with huge multilingual and bilingual population, this hate content would be in code-mixed form which makes the task demanding. So our paper projects a machine learning model to detect hate speech in Hindi-English code-mixed social media text. The methodology makes use of Facebook’s pre-trained word embedding library, fastText to represent 10000 data samples collected from different sources as hate and non-hate. The performance of the proposed methodology is compared with word2vec and doc2vec features and it is observed that fastText features gave better feature representation with Support Vector Machine (SVM)-Radial Basis Funcrion (RBF) classifier. The paper also provides an insight to the researchers working in the field of code-mixed data that character level features provide best result for code-mixed data.

The ubiquitous nature of social media platforms resulted into generation of large amount of multimedia data in social networks. The openness and unrestricted way to share the information on social media platforms fosters information spread across the network regardless of its credibility. Such kind of spreading the misinformation happens usually in the context of breaking news. Due to unverified information, such misinformation, also known as rumors may cause severe damages. Despite overwhelming use, uncontrolled nature of social media platforms usually results in generation and unfold of rumors. Therefore, automatically detecting the rumors from social media platforms is one of the highly sought-after research area in the domain of social media analytics. Motivated by the same, this paper focuses on detailed discussion of datasets and state-of-the-art approaches of rumor detection. Moreover, this paper sheds light upon supervised and unsupervised methods and deep learning approaches for rumor detection.

It is known that social media is one of the largest sources of unstructured data. Analyzing that data and harvesting meaning out of that is a tedious job. Recently opinion mining has become an emerging topic due to the vast amount of opinioned data available on the various social networking sites. Microblogging has appeared relatively recently, and twitter is the most popular microblogging sites used by the people. It is one of the biggest free, open data-source. In the world today, twitter often witnesses a lot of opinions. Opinion mining and sentiment analysis help researchers to gain insight into public emotions. In this paper, Twitter is used as a source of opinioned data. Twitter APIs are used for the collection of tweets. In this paper, R is used for the acquisition, pre- processing, analyzing the tweets, then sentiment analysis is performed based on the different approaches. In this paper, Tweets were collected from the period of Jan 2019 to March 2019. Using that tweets, sentiment analysis was performed to gain the opinion polarity of the folks concerning general elections held in India. Two candidates were considered for this study: Candidate-1 and Candidate-2. It was concluded that Candidate-1 is more liked and is famous as compared to Candidate-2. The result obtained in our paper was in full compliance with the actual election results obtained in May 2019.