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This paper contributes to the social theoretical foundations of a sociology of media and communication by making use of the cultural–historical school in psychology. Such perspective gains relevance in digital capitalism and the blurring of production and Internet usage. The paper first revisits Habermas's influential notion of communicative action and agency. Second, it uses activity theory as an alternative, more promising way of theorising because it links communication closer to work. A model of communicative action is introduced and a conceptual link between media and human tool use is established. Third, the paper elaborates on the notion of activity in the digital world and posits that digitalisation can be understood as a 'machinisation' of mental and communicative-coordinative work. The developed perspective, the paper concludes, allows critical media and communication sociology to operate with meaningful concepts of communicative expropriation, exploitation and alienation. [ABSTRACT FROM AUTHOR]

Just as the Frankfurt School responded to the radicalisation of the working class in Germany and the rise of post-war consumerism in the United States, today, we are confronted by platform monopolies, automated hyper-consumption and technological control. Critical approaches to digital media have exposed the structural coupling of Internet use and capital accumulation for almost two decades. However, many authors building on this tradition can struggle to understand how online social interaction is controlled beyond the worn-out critique of false consciousness or beyond conceptualising all digital activity mediated by data as labour. This paper will attempt to theoretically untangle the Marxian ontology of labour and the Frankfurt School-inspired critique of everyday life. This is not just theoretical nit-picking. Society becomes completely dominated if we accept no difference between wage labour and lifeworld activities. Each contains its internal struggles. The value form regulates both in different ways. [ABSTRACT FROM AUTHOR]

In the sociology of education, opponents of deficit thinking would be seen as important change agents, potentially inspiring radical policy change aimed at reducing systemic discrimination of specific sociodemographic groups. That is, contestation of deficit thinking can in theory lead to its destruction. In this paper, we argue that contestation can be overruled or downplayed via public discourses. From a discourse-historical approach, we illustrate how contestation was attenuated in the context of ethnicity in Flemish higher education in the period 1985–2020. We show how a variety of discursive processes eventually marginalize anti-deficit narratives in mass media texts, even though these stances were dominant at certain moments. The major contribution of our study is that it highlights important discursive mechanisms underlying the reproduction of deficit thinking in times of contestation. [ABSTRACT FROM AUTHOR]

Child marriage is a problem that has continued to attract global attention. The media have been identified as critical to the fight against the scourge as it discusses the capacity to raise awareness of the issue as well as trigger action in solving the problem. The report of the alleged abduction of a minor, Ese Oruru by one Yunusa Dahiru for marriage jolted the nation and sparked public outcry for her release. This study explored newspaper framing of the incident. Drawing from qualitative frame analysis, it examined how Punch and Daily Trust newspapers framed the alleged abduction saga. The study found that there was contrastive framing of the incident with Punch newspaper portraying the issue as abduction while Daily Trust newspaper depicted it as elopement. The influence of socio-cultural leanings of these papers on the contrastive framing is discussed. The implication of the divergent framing of the saga on the fight against child marriage is highlighted. [ABSTRACT FROM AUTHOR]

The article presents guidelines for submitting papers for publication in the "Society in Transition," the journal of the South African Sociological Association. Three paper copies must be submitted. An electronic copy of the final version of the manuscript can be sent by email to the scientific editor. The first page should contain the following: title of the article, the author's name, address, email address and the abstract. Each article must be preceded by a short abstract and a short list of five important keywords should be provided.

The last several decades have witnessed a shift in the way in which news is delivered and consumed by users. With the growth and advancements in mobile technologies, the Internet, and Web 2.0 technologies users are not only consumers of news, but also producers of online content. This has resulted in a novel and highly participatory cyber-physical news awareness ecosystem that fosters digital activism, in which volunteers contribute content to online communities. While studies have examined the various components of this news awareness ecosystem, little is still known about how news media coverage (and in particular digital media) impacts digital activism. In order to address this challenge and develop a greater understanding of it, this paper focuses on a specific form of digital activism, that of the production of digital geographical content through crowdsourcing efforts. Using refugee camps from around the world as a case study, we examine the relationship between news coverage (via Google news), search trends (via Google trends) and user edit contribution patterns in OpenStreetMap, a prominent geospatial data crowdsourcing platform. In addition, we compare and contrast these patterns with user edit patterns in Wikipedia, a well-known non-geospatial crowdsourcing platform. Using Google news and Google trends to derive a measure of thematic public awareness, our findings indicate that digital activism bursts tend to take place during periods of sustained build-up of public awareness deficit or surplus. These findings are in line with two prominent mass communication theories: agenda setting and corrective action, and suggest the emergence of a novel stimulus-awareness-activism framework in today’s participatory digital age. Moreover, these findings further complement existing research examining the motivational factors that drive users to contribute to online collaborative communities. This paper brings us one step closer to understanding the underlying mechanisms that drive digital activism in particular in the geospatial domain. [ABSTRACT FROM AUTHOR]

As researchers use computational methods to study complex social behaviors at scale, the validity of this computational social science depends on the integrity of the data. On July 2, 2015, Jason Baumgartner published a dataset advertised to include “every publicly available Reddit comment” which was quickly shared on Bittorrent and the Internet Archive. This data quickly became the basis of many academic papers on topics including machine learning, social behavior, politics, breaking news, and hate speech. We have discovered substantial gaps and limitations in this dataset which may contribute to bias in the findings of that research. In this paper, we document the dataset, substantial missing observations in the dataset, and the risks to research validity from those gaps. In summary, we identify strong risks to research that considers user histories or network analysis, moderate risks to research that compares counts of participation, and lesser risk to machine learning research that avoids making representative claims about behavior and participation on Reddit. [ABSTRACT FROM AUTHOR]

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user’s credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method. [ABSTRACT FROM AUTHOR]

This essay starts from the premise that sociological analysis has made important and valuable contributions to the conceptualization of the cultural, moral, and institutional aspects of communication. At present, however, the contributions of the sociology seem poorly represented within the field of communicative studies because these commonly overlook the fact that digital communication is inextricably linked to the social and material spaces which humans act and interact. Considering that it can generate a necessarily limited understanding of the communicative phenomenon, the objective of this work is to explore the approaches proposed by five schools of thought regarding the sociology of communication. Firstly, this paper reviews the main works produced by the Chicago School, the Columbia School, the Frankfurt School, the Toronto School and the Birmingham School to try to elucidate the conceptual bases of their postulates and to understand the criticisms they received from other scholars in the field. Subsequently, it describes the historical changes of the disciplinary research program and the approaches through which social researchers are trying to recognize and to understand the complex sociotechnical assemblages that characterize contemporary communication. Finally, it argues that the sociological perspective continues to be substantial in developing a critical comprehension of the social, political, and economic impact of digital mediatization. [ABSTRACT FROM AUTHOR]

This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end-to-end coreference resolution system for the Basque language. The adaptation process explained can benefit and facilitate other languages with similar characteristics in the implementation of their coreference resolution systems. During the experimentation phase, we have demonstrated that language-specific features have a noteworthy effect on coreference resolution, obtaining a gain in CoNLL score of 7.07 with respect to the baseline system. We have also analysed the effect that preprocessing has in coreference resolution, comparing the results obtained with automatic mentions versus gold mentions. When gold mentions are provided, the results increase 11.5 points in CoNLL score in comparison with results obtained when automatic mentions are used. The contribution of each sieve is analysed concluding that morphology is essential for agglutinative languages to obtain good performance in coreference resolution. Finally, an error analysis of the coreference resolution system is presented which have revealed our system’s weak points and help to determine the improvements of the system. As a result of the error analysis, we have enriched the Basque coreference resolution adding new two sieves, obtaining an improvement of 0.24 points in CoNLL F1 when automatic mentions are used and of 0.39 points when the gold mentions are provided. [ABSTRACT FROM AUTHOR]

In this paper, we propose to analyze the conditions in which Antonio Pasquali approached, between the mid-sixties and the beginning of the seventies, the philosophical and sociological reflections elaborated by the Frankfurt School. From a theoretical-methodological framework inscribed in the sociology of culture, the cultural and intellectual networks in which the Venezuelan theorist participated are reconstructed. This analytical input allows us to account certain readings and appropriations of the so-called "critical theory of society", in a specific context about the discussions about the relationship between communication, culture and the mass media. [ABSTRACT FROM AUTHOR]

Interest in modeling contemporary crime trends, a task that has historically been considered valuable to the public, researchers, and policymakers, is resurging. Advancements in criminology have made it clear that understanding crime trends necessarily involves understanding trends in how likely individuals are to report crimes to the police, as well as how likely the police are to accurately record those crimes. In this paper, we use dynamic linear models to simultaneously model the time series for several crime types in order to gain insight into trends in crime and crime reporting. We analyze crime data from Chicago spanning 2007 through 2016 and show how correlations in the way crime trends evolve may contain information about drivers of crime and crime reporting. We provide evidence of substantial differences in the relationships between the trends of crimes of different types depending on whether crimes are violent or nonviolent and whether or not crimes are tracked in the FBI’s Uniform Crime Report. [ABSTRACT FROM AUTHOR]

How can we extract hidden relations from a tensor and a matrix data simultaneously in a fast, accurate, and scalable way? Coupled matrix-tensor factorization (CMTF) is an important tool for this purpose. Designing an accurate and efficient CMTF method has become more crucial as the size and dimension of real-world data are growing explosively. However, existing methods for CMTF suffer from lack of accuracy, slow running time, and limited scalability. In this paper, we propose S3CMTF, a fast, accurate, and scalable CMTF method. In contrast to previous methods which do not handle large sparse tensors and are not parallelizable, S3CMTF provides parallel sparse CMTF by carefully deriving gradient update rules. S3CMTF asynchronously updates partial gradients without expensive locking. We show that our method is guaranteed to converge to a quality solution theoretically and empirically. S3CMTF further boosts the performance by carefully storing intermediate computation and reusing them. We theoretically and empirically show that S3CMTF is the fastest, outperforming existing methods. Experimental results show that S3CMTF is up to 930× faster than existing methods while providing the best accuracy. S3CMTF shows linear scalability on the number of data entries and the number of cores. In addition, we apply S3CMTF to Yelp rating tensor data coupled with 3 additional matrices to discover interesting patterns. [ABSTRACT FROM AUTHOR]

Given a real-world graph, how can we measure relevance scores for ranking and link prediction? Random walk with restart (RWR) provides an excellent measure for this and has been applied to various applications such as friend recommendation, community detection, anomaly detection, etc. However, RWR suffers from two problems: 1) using the same restart probability for all the nodes limits the expressiveness of random walk, and 2) the restart probability needs to be manually chosen for each application without theoretical justification. We have two main contributions in this paper. First, we propose R W E R (RWER), a random walk based measure which improves the expressiveness of random walks by using a distinct restart probability for each node. The improved expressiveness leads to superior accuracy for ranking and link prediction. Second, we propose SR (pervised start for RWER), an algorithm for learning the restart probabilities of RWER from a given graph. SR eliminates the need to heuristically and manually select the restart parameter for RWER. Extensive experiments show that our proposed method provides the best performance for ranking and link prediction tasks. [ABSTRACT FROM AUTHOR]

The ability to produce timely and accurate flu forecasts in the United States can significantly impact public health. Augmenting forecasts with internet data has shown promise for improving forecast accuracy and timeliness in controlled settings, but results in practice are less convincing, as models augmented with internet data have not consistently outperformed models without internet data. In this paper, we perform a controlled experiment, taking into account data backfill, to improve clarity on the benefits and limitations of augmenting an already good flu forecasting model with internet-based nowcasts. Our results show that a good flu forecasting model can benefit from the augmentation of internet-based nowcasts in practice for all considered public health-relevant forecasting targets. The degree of forecast improvement due to nowcasting, however, is uneven across forecasting targets, with short-term forecasting targets seeing the largest improvements and seasonal targets such as the peak timing and intensity seeing relatively marginal improvements. The uneven forecasting improvements across targets hold even when “perfect” nowcasts are used. These findings suggest that further improvements to flu forecasting, particularly seasonal targets, will need to derive from other, non-nowcasting approaches. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between candidates’ online popularity and election results, as a step towards creating a model to forecast the results of Taiwanese elections even in the absence of reliable opinion polls on a district-by-district level. 253 of 354 legislative candidates of single-member districts in Taiwan’s 2016 general election had active public Facebook pages during the election period. Hypothesizing that the relative popularity of candidates’ Facebook posts will be positively related to their election results, I calculated each candidate’s Like Ratio (i.e. proportions of all likes on Facebook posts obtained by candidates in their district). In order to have a measure of online interest without the influence of subjective positivity, I similarly calculated the proportion of daily average page views for each candidate’s Wikipedia page. I ran a regression analysis, incorporating data on results of previous elections and available opinion poll data. I found the models could describe the result of the election well and reject the null hypothesis. My models successfully predicted 80% of winners in single-member districts and were effective in districts without local opinion polls with a predictive power approaching that of traditional opinion polls. The models also showed good accuracy when run on data for the 2014 Taiwanese municipal mayors election. [ABSTRACT FROM AUTHOR]

Interactions between countries originate from diverse aspects such as geographic proximity, trade, socio-cultural habits, language, religions, etc. Geopolitics studies the influence of a country’s geographic space on its political power and its relationships with other countries. This work reveals the potential of Wikipedia mining for geopolitical study. Actually, Wikipedia offers solid knowledge and strong correlations among countries by linking web pages together for different types of information (e.g. economical, historical, political, and many others). The major finding of this paper is to show that meaningful results on the influence of country ties can be extracted from the hyperlinked structure of Wikipedia. We leverage a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory. For a selected small size set of nodes, the reduced Google matrix concentrates direct and indirect links of the million-node sized Wikipedia network into a small Perron-Frobenius matrix keeping the PageRank probabilities of the global Wikipedia network. We perform a novel sensitivity analysis that leverages this reduced Google matrix to characterize the influence of relationships between countries from the global network. We apply this analysis to two chosen sets of countries (i.e. the set of 27 European Union countries and a set of 40 top worldwide countries). We show that with our sensitivity analysis we can exhibit easily very meaningful information on geopolitics from five different Wikipedia editions (English, Arabic, Russian, French and German). [ABSTRACT FROM AUTHOR]

Neuroscience research on sex difference is currently a controversial field, frequently accused of purveying a ‘neurosexism’ that functions to naturalise gender inequalities. However, there has been little empirical investigation of how information about neurobiological sex difference is interpreted within wider society. This paper presents a case study that tracks the journey of one high-profile study of neurobiological sex differences from its scientific publication through various layers of the public domain. A content analysis was performed to ascertain how the study was represented in five domains of communication: the original scientific article, a press release, the traditional news media, online reader comments and blog entries. Analysis suggested that scientific research on sex difference offers an opportunity to rehearse abiding cultural understandings of gender. In both scientific and popular contexts, traditional gender stereotypes were projected onto the novel scientific information, which was harnessed to demonstrate the factual truth and normative legitimacy of these beliefs. Though strains of misogyny were evident within the readers’ comments, most discussion of the study took pains to portray the sexes’ unique abilities as equal and ‘complementary’. However, this content often resembled a form of benevolent sexism, in which praise of women’s social-emotional skills compensated for their relegation from more esteemed trait-domains, such as rationality and productivity. The paper suggests that embedding these stereotype patterns in neuroscience may intensify their rhetorical potency by lending them the epistemic authority of science. It argues that the neuroscience of sex difference does not merely reflect, but can actively shape the gender norms of contemporary society. [ABSTRACT FROM AUTHOR]

Deep learning techniques, e.g., Convolutional Neural Networks (CNNs), have been explosively applied to the research in the fields of information retrieval and natural language processing. However, few research efforts have addressed semantic indexing with deep learning. The use of semantic indexing in the biomedical literature has been limited for several reasons. For instance, MEDLINE citations contain a large number of semantic labels from automatically annotated MeSH terms, and for a great deal of the literature, only the information of the title and the abstract is readily available. In this paper, we propose a Boltzmann Convolutional neural network framework (B-CNN) for biomedicine semantic indexing. In our hybrid learning framework, the CNN can adaptively deal with features of documents that have sequence relationships, and can capture context information accordingly; the Deep Boltzmann Machine (DBM) merges global (the entity in each document) and local information through its training with undirected connections. Additionally, we have designed a hierarchical coarse to fine style indexing structure for learning and classifying documents, and a novel feature extension approach with word sequence embedding and Wikipedia categorization. Comparative experiments were conducted for semantic indexing of biomedical abstract documents; these experiments verified the encouraged performance of our B-CNN model. [ABSTRACT FROM AUTHOR]

Despite both scholarly and popular claims that citizen journalism (CJ) represents a growing democratizing force in the journalistic field, recent scholarship in the area has noted the decline of the organizational population of CJ. In this paper, we investigate how individual characteristics of sites and the dynamics of larger organizational population affect a CJ site’s risk of experiencing a mortality. Drawing on the largest sample to date of US-based English-language CJ sites, this study examines the risk of site mortality through an event history framework. Findings indicate that the strongest predictor of a site’s mortality is the age of the site, consistent with organizational population theory’s ‘liability of newness.’ We also find that for-profit and community-based sites have lower rates of site mortality, indicating that adopting legitimate conventions of journalism may serve as a protective buffer to site death. The results offer mixed evidence on whether CJ has become more professionalized via attrition. [ABSTRACT FROM AUTHOR]

Cryptocurrencies have experienced recent surges in interest and price. It has been discovered that there are time intervals where cryptocurrency prices and certain online and social media factors appear related. In addition it has been noted that cryptocurrencies are prone to experience intervals of bubble-like price growth. The hypothesis investigated here is that relationships between online factors and price are dependent on market regime. In this paper, wavelet coherence is used to study co-movement between a cryptocurrency price and its related factors, for a number of examples. This is used alongside a well-known test for financial asset bubbles to explore whether relationships change dependent on regime. The primary finding of this work is that medium-term positive correlations between online factors and price strengthen significantly during bubble-like regimes of the price series; this explains why these relationships have previously been seen to appear and disappear over time. A secondary finding is that short-term relationships between the chosen factors and price appear to be caused by particular market events (such as hacks / security breaches), and are not consistent from one time interval to another in the effect of the factor upon the price. In addition, for the first time, wavelet coherence is used to explore the relationships between different cryptocurrencies. [ABSTRACT FROM AUTHOR]

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia—an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system. [ABSTRACT FROM AUTHOR]

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf’s law and Heaps’ law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf’s law and Heaps’ law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks. [ABSTRACT FROM AUTHOR]

This paper demonstrates a framework of processes for identifying potential witnesses of events from evidence they post to social media. The research defines original evidence models for micro-blog content sources, the relative uncertainty of different evidence types, and models for testing evidence by combination. Methods to filter and extract evidence using automated and semi-automated means are demonstrated using a Twitter case study event. Further, an implementation to test extracted evidence using Dempster Shafer Theory of Evidence are presented. The results indicate that the inclusion of evidence from micro-blog text and linked image content can increase the number of micro-bloggers identified at events, in comparison to the number of micro-bloggers identified from geotags alone. Additionally, the number of micro-bloggers that can be tested for evidence corroboration or conflict, is increased by incorporating evidence identified in their posting history. [ABSTRACT FROM AUTHOR]

Online Social Networks generate a prodigious wealth of real-time information at an incessant rate. In this paper we study the empirical data that crawled from Twitter to describe the topology and information spreading dynamics of Online Social Networks. We propose a measurement with three measures to state the efforts of users on Twitter to get their information spreading, based on the unique mechanisms for information retransmission on Twitter. It is noticed that small fraction of users with special performance on participation can gain great influence, while most other users play a role as middleware during the information propagation. Thus a community analysis is performed and four categories of users are found with different kinds of participation that cause the information dissemination dynamics. These suggest that exiting topological measures alone may reflect little about the influence of individuals and provide new insights for information spreading. [ABSTRACT FROM AUTHOR]

Over the history of mankind, textual records change. Sometimes due to mistakes during transcription, sometimes on purpose, as a way to rewrite facts and reinterpret history. There are several classical cases, such as the logarithmic tables, and the transmission of antique and medieval scholarship. Today, text documents are largely edited and redistributed on the Web. Articles on news portals and collaborative platforms (such as Wikipedia), source code, posts on social networks, and even scientific publications or literary works are some examples in which textual content can be subject to changes in an evolutionary process. In this scenario, given a set of near-duplicate documents, it is worthwhile to find which one is the original and the history of changes that created the whole set. Such functionality would have immediate applications on news tracking services, detection of plagiarism, textual criticism, and copyright enforcement, for instance. However, this is not an easy task, as textual features pointing to the documents’ evolutionary direction may not be evident and are often dataset dependent. Moreover, side information, such as time stamps, are neither always available nor reliable. In this paper, we propose a framework for reliably reconstructing text phylogeny trees, and seamlessly exploring new approaches on a wide range of scenarios of text reusage. We employ and evaluate distinct combinations of dissimilarity measures and reconstruction strategies within the proposed framework, and evaluate each approach with extensive experiments, including a set of artificial near-duplicate documents with known phylogeny, and from documents collected from Wikipedia, whose modifications were made by Internet users. We also present results from qualitative experiments in two different applications: text plagiarism and reconstruction of evolutionary trees for manuscripts (stemmatology). [ABSTRACT FROM AUTHOR]

This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds. [ABSTRACT FROM AUTHOR]

Background: Building or maintaining institutional trust is of central importance in democratic societies since negative experiences (potentially leading to mistrust) with government or other institutions may have a much more profound effect than positive experiences (potentially maintaining trust). Healthy democracy relies on more than simply trusting the national government of the time, and is mediated through other symbols of institutional power, such as the legal system, banks, the media and religious organisations. This paper focuses on institutional trust–the level and predictors of trust in some of the major institutions in society, namely politics, the media, banks, the legal system and religious organisations. We present analyses from a consolidated dataset containing data from six countries in the Asia Pacific region–Australia, Hong Kong, Japan, South Korea, Taiwan and Thailand. Methods: Cross-sectional surveys were undertaken in each country in 2009–10, with an overall sample of 6331. Analyses of differences in overall levels of institutional trust between countries were undertaken using Chi square analyses. Multivariate binomial logistic regression analysis was undertaken to identify socio-demographic predictors of trust in each country. Results: Religious institutions, banks and the judicial system had the highest overall trust across all countries (70%, 70% and 67% respectively), followed by newspapers and TV (59% and 58%) and then political leaders (43%). The range of levels of higher trust between countries differed from 43% for banks (range 49% in Australia to 92% in Thailand) to 59% for newspapers (28% in Australia to 87% in Japan). Across all countries, except for Australia, trust in political leaders had the lowest scores, particularly in Japan and South Korea (25% in both countries). In Thailand, people expressed the most trust in religious organisations (94%), banks (92%) and in their judicial/legal system (89%). In Hong Kong, people expressed the highest level of trust in their judicial/legal system (89%), followed by religious organisations (75%) and banks (77%). Australian respondents reported the least amount of trust in TV/media (24%) and press/newspapers (28%). South Korea put the least trust in their political leaders (25%), their legal system (43%) and religious organisations (45%). The key predictors of lower trust in institutions across all countries were males, people under 44 years and people unsatisfied with the health and standard of living. Conclusion: We interpreted our data using Fukuyama’s theory of ‘high/low trust’ societies. The levels of institutional trust in each society did not conform to our hypothesis, with Thailand exhibiting the highest trust (predicted to be medium level), Hong Kong and Japan exhibiting medium trust (predicted to be low and high respectively) and Australia and South Korea exhibiting low trust (predicted to be high and medium respectively). Taiwan was the only country where the actual and predicted trust was the same, namely low trust. Given the fact that these predictors crossed national boundaries and institutional types, further research and policy should focus specifically on improving trust within these groups in order that they can be empowered to play a more central role in democratic vitality. [ABSTRACT FROM AUTHOR]

Previous researches support that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Moreover, literature shows that different types of graphical information can help or harm the accuracy on decision making of accountants and financial analysts. We conducted a 4×2 mixed-design experiment to examine the effects of numerical information disclosure on financial analysts’ accuracy, and investigated the role of overconfidence in decision making. Results show that compared to text, column graph enhanced accuracy on decision making, followed by line graphs. No difference was found between table and textual disclosure. Overconfidence harmed accuracy, and both genders behaved overconfidently. Additionally, the type of disclosure (text, table, line graph and column graph) did not affect the overconfidence of individuals, providing evidence that overconfidence is a personal trait. This study makes three contributions. First, it provides evidence from a larger sample size (295) of financial analysts instead of a smaller sample size of students that graphs are relevant decision aids to tasks related to the interpretation of numerical information. Second, it uses the text as a baseline comparison to test how different ways of information disclosure (line and column graphs, and tables) can enhance understandability of information. Third, it brings an internal factor to this process: overconfidence, a personal trait that harms the decision-making process of individuals. At the end of this paper several research paths are highlighted to further study the effect of internal factors (personal traits) on financial analysts’ accuracy on decision making regarding numerical information presented in a graphical form. In addition, we offer suggestions concerning some practical implications for professional accountants, auditors, financial analysts and standard setters. [ABSTRACT FROM AUTHOR]

The rich get richer principle, manifested by the Preferential attachment (PA) mechanism, is widely considered one of the major factors in the growth of real-world networks. PA stipulates that popular nodes are bound to be more attractive than less popular nodes; for example, highly cited papers are more likely to garner further citations. However, it overlooks the transient nature of popularity, which is often governed by trends. Here, we show that in a wide range of real-world networks the recent popularity of a node, i.e., the extent by which it accumulated links recently, significantly influences its attractiveness and ability to accumulate further links. We proceed to model this observation with a natural extension to PA, named Trending Preferential Attachment (TPA), in which edges become less influential as they age. TPA quantitatively parametrizes a fundamental network property, namely the network’s tendency to trends. Through TPA, we find that real-world networks tend to be moderately to highly trendy. Networks are characterized by different susceptibilities to trends, which determine their structure to a large extent. Trendy networks display complex structural traits, such as modular community structure and degree-assortativity, occurring regularly in real-world networks. In summary, this work addresses an inherent trait of complex networks, which greatly affects their growth and structure, and develops a unified model to address its interaction with preferential attachment. [ABSTRACT FROM AUTHOR]

This paper examines the construction of avian influenza in Australian media and federal government policy, with a focus placed on discourses of contagion, preparedness and risk. The threat of an infectious disease outbreak, such as avian influenza, on social life is surrounded by a range of collective narratives which attempt to make it explicable. These narratives socially define the disease and provide explanations for its existence. The paper demonstrates that central to these narratives are depictions of the source of the outbreak and suggestions of appropriate responses to the threat. Methodologically, a narrative analysis of print media and government documents was conducted. This showed that conceptually both government and media discourses could be understood in terms of risk, contagion and blame. Furthermore, it was found that narratives linking the risk of avian influenza with globalised interconnectedness and contagion by the developing world underpin discourses of causation and frame the reactions to and preparation for a potential outbreak. [ABSTRACT FROM AUTHOR]

This study examines disability terminology to explore how the news media frame cultural representations of the disability community. More specifically, the paper examines the impact of the Americans with Disabilities Act on journalist's language choices about disability topics. A content analysis of news stories using disability terms in The Washington Post and The New York Times during the past decade was conducted. The paper illustrates that disability community identity continues to be formed, transformed and maintained through news media presentations of disability terminology. The paper argues that the US Disability Rights Movement had some success during the 1990s in putting forth language that advances its aims, though the study also suggests that some journalists continue to use terms that perpetuate limiting, narrow stereotypes about people with disabilities. [ABSTRACT FROM AUTHOR]

In a connected world where people influence each other, what can cause a globalized monoculture, and which measures help to preserve the coexistence of cultures? Previous research has shown that factors such as homophily, population size, geography, mass media, and type of social influence play important roles. In the present paper, we investigate for the first time the impact that institutions have on cultural diversity. In our first three studies, we extend existing agent-based models and explore the effects of institutional influence and agent loyalty. We find that higher institutional influence increases cultural diversity, while individuals' loyalty to their institutions has a small, preserving effect. In three further studies, we test how bottom-up and top-down processes of institutional influence impact our model. We find that bottom-up democratic practices, such as referenda, tend to produce convergence towards homogeneity, while top-down information dissemination practices, such as propaganda, further increase diversity. In our last model—an integration of bottom-up and top-down processes into a feedback loop of information—we find that when democratic processes are rare, the effects of propaganda are amplified, i.e., more diversity emerges; however, when democratic processes are common, they are able to neutralize or reverse this propaganda effect. Importantly, our models allow for control over the full spectrum of diversity, so that a manipulation of our parameters can result in preferred levels of diversity, which will be useful for the study of other factors in the future. We discuss possible mechanisms behind our results, applications, and implications for political and social sciences. [ABSTRACT FROM AUTHOR]

Place can be generally defined as a location that has been assigned meaning through human experience, and as such it is of multidisciplinary scientific interest. Up to this point place has been studied primarily within the context of social sciences as a theoretical construct. The availability of large amounts of user-generated content, e.g. in the form of social media feeds or Wikipedia contributions, allows us for the first time to computationally analyze and quantify the shared meaning of place. By aggregating references to human activities within urban spaces we can observe the emergence of unique themes that characterize different locations, thus identifying places through their discernible sociocultural signatures. In this paper we present results from a novel quantitative approach to derive such sociocultural signatures from Twitter contributions and also from corresponding Wikipedia entries. By contrasting the two we show how particular thematic characteristics of places (referred to herein as platial themes) are emerging from such crowd-contributed content, allowing us to observe the meaning that the general public, either individually or collectively, is assigning to specific locations. Our approach leverages probabilistic topic modelling, semantic association, and spatial clustering to find locations are conveying a collective sense of place. Deriving and quantifying such meaning allows us to observe how people transform a location to a place and shape its characteristics. [ABSTRACT FROM AUTHOR]

This paper uses original survey data of the Great East Japan earthquake disaster victims to examine their decision to apply for the temporary housing as well as the timing of application. We assess the effects of victims’ attachment to their locality as well as variation in victims’ information seeking behavior. We additionally consider various factors such as income, age, employment and family structure that are generally considered to affect the decision to choose temporary housing as victims’ solution for their displacement. Empirical results indicate that, ceteris paribus, as the degree of attachment increases, victims are more likely to apply for the temporary housing but attachment does not affect the timing of application. On the other hand, the victims who actively seek information and are able to collect higher quality information are less likely to apply for the temporary housing and if they do apply then they apply relatively later. [ABSTRACT FROM AUTHOR]

Twitter is an extremely high volume platform for user generated contributions regarding any topic. The wealth of content created at real-time in massive quantities calls for automated approaches to identify the topics of the contributions. Such topics can be utilized in numerous ways, such as public opinion mining, marketing, entertainment, and disaster management. Towards this end, approaches to relate single or partial posts to knowledge base items have been proposed. However, in microblogging systems like Twitter, topics emerge from the culmination of a large number of contributions. Therefore, identifying topics based on collections of posts, where individual posts contribute to some aspect of the greater topic is necessary. Models, such as Latent Dirichlet Allocation (LDA), propose algorithms for relating collections of posts to sets of keywords that represent underlying topics. In these approaches, figuring out what the specific topic(s) the keyword sets represent remains as a separate task. Another issue in topic detection is the scope, which is often limited to specific domain, such as health. This work proposes an approach for identifying domain-independent specific topics related to sets of posts. In this approach, individual posts are processed and then aggregated to identify key tokens, which are then mapped to specific topics. Wikipedia article titles are selected to represent topics, since they are up to date, user-generated, sophisticated articles that span topics of human interest. This paper describes the proposed approach, a prototype implementation, and a case study based on data gathered during the heavily contributed periods corresponding to the four US election debates in 2012. The manually evaluated results (0.96 precision) and other observations from the study are discussed in detail. [ABSTRACT FROM AUTHOR]

As breaking news unfolds people increasingly rely on social media to stay abreast of the latest updates. The use of social media in such situations comes with the caveat that new information being released piecemeal may encourage rumours, many of which remain unverified long after their point of release. Little is known, however, about the dynamics of the life cycle of a social media rumour. In this paper we present a methodology that has enabled us to collect, identify and annotate a dataset of 330 rumour threads (4,842 tweets) associated with 9 newsworthy events. We analyse this dataset to understand how users spread, support, or deny rumours that are later proven true or false, by distinguishing two levels of status in a rumour life cycle i.e., before and after its veracity status is resolved. The identification of rumours associated with each event, as well as the tweet that resolved each rumour as true or false, was performed by journalist members of the research team who tracked the events in real time. Our study shows that rumours that are ultimately proven true tend to be resolved faster than those that turn out to be false. Whilst one can readily see users denying rumours once they have been debunked, users appear to be less capable of distinguishing true from false rumours when their veracity remains in question. In fact, we show that the prevalent tendency for users is to support every unverified rumour. We also analyse the role of different types of users, finding that highly reputable users such as news organisations endeavour to post well-grounded statements, which appear to be certain and accompanied by evidence. Nevertheless, these often prove to be unverified pieces of information that give rise to false rumours. Our study reinforces the need for developing robust machine learning techniques that can provide assistance in real time for assessing the veracity of rumours. The findings of our study provide useful insights for achieving this aim. [ABSTRACT FROM AUTHOR]

This paper presents data from the Program for the International Assessment of Adult Competencies with a focus on the interrelationships among health information seeking behavior (HISB), and health status or use of preventive health measures for U.S. adults both with and without a high school diploma. Key results of ordinal and binary logistic regression analyses indicated that, after controlling for demographic factors, (1) adults with a high school diploma use more text-based health information sources while adults without a high school diploma use more oral sources, (2) using the Internet as a source of health information is more strongly related to reporting excellent/very good health status than having a high school diploma, (3) those without a high school diploma who use the Internet report the largest increase in health status over any other health information source, and (4) for those with learning disability or vision problem, a high facility in reading English is an important predictor of whether the Internet is used as a health information source. The Internet appears to play a key role in both enhancing health status and enabling use of preventive measures for those with and without a high school diploma; although, individuals without a high school diploma who use the Internet for health information derive substantial benefit in health status. [ABSTRACT FROM AUTHOR]

Graphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually finding all graphlets in a large graph can be time-consuming, however. As the graphlets grow in size, more different graphlets emerge and the time needed to find each graphlet also scales up. If it is not needed to find each instance of each graphlet, but knowing the number of graphlets touching each node of the graph suffices, the problem is less hard. Previous research shows a way to simplify counting the graphlets: instead of looking for the graphlets needed, smaller graphlets are searched, as well as the number of common neighbors of vertices. Solving a system of equations then gives the number of times a vertex is part of each graphlet of the desired size. However, until now, equations only exist to count graphlets with 4 or 5 nodes. In this paper, two new techniques are presented. The first allows to generate the equations needed in an automatic way. This eliminates the tedious work needed to do so manually each time an extra node is added to the graphlets. The technique is independent on the number of nodes in the graphlets and can thus be used to count larger graphlets than previously possible. The second technique gives all graphlets a unique ordering which is easily extended to name graphlets of any size. Both techniques were used to generate equations to count graphlets with 4, 5 and 6 vertices, which extends all previous results. Code can be found at and . [ABSTRACT FROM AUTHOR]

Screen media usage, sleep time and socio-demographic features are related to adolescents' academic performance, but interrelations are little explored. This paper describes these interrelations and behavioral profiles clustered in low and high academic performance. A nationally representative sample of 3,095 Spanish adolescents, aged 12 to 18, was surveyed on 15 variables linked to the purpose of the study. A Self-Organizing Maps analysis established non-linear interrelationships among these variables and identified behavior patterns in subsequent cluster analyses. Topological interrelationships established from the 15 emerging maps indicated that boys used more passive videogames and computers for playing than girls, who tended to use mobile phones to communicate with others. Adolescents with the highest academic performance were the youngest. They slept more and spent less time using sedentary screen media when compared to those with the lowest performance, and they also showed topological relationships with higher socioeconomic status adolescents. Cluster 1 grouped boys who spent more than 5.5 hours daily using sedentary screen media. Their academic performance was low and they slept an average of 8 hours daily. Cluster 2 gathered girls with an excellent academic performance, who slept nearly 9 hours per day, and devoted less time daily to sedentary screen media. Academic performance was directly related to sleep time and socioeconomic status, but inversely related to overall sedentary screen media usage. Profiles from the two clusters were strongly differentiated by gender, age, sedentary screen media usage, sleep time and academic achievement. Girls with the highest academic results had a medium socioeconomic status in Cluster 2. Findings may contribute to establishing recommendations about the timing and duration of screen media usage in adolescents and appropriate sleep time needed to successfully meet the demands of school academics and to improve interventions targeting to affect behavioral change. [ABSTRACT FROM AUTHOR]

For Max Weber the goal of social science was to improve our knowledge of cultural problems. The newspaper industry at the turn of the 19th century was for him one of the 'great cultural problems of the present' (Weber 1998: 111). When he presented his plan for a sociological investigation of the press to the German Sociological Society in 1910, the newspaper industry in Europe was emerging from over a half-century of change that was at least as profound in its social and political implications as those resulting from the changes taking place in the global news industries of today. By 1910 the processes of rationalization were beginning to raise questions about journalistic practices and the role of the press in the formation and orchestration of public opinion. The importance of journalists and the news industry as research topics must have been as obvious to Weber and his colleagues at that time as it is to contemporary media scholars. This paper discusses Weber's plan and the continuities that can be traced from it through media sociology's various attempts to address the issue of public opinion and the practice of journalism. [ABSTRACT FROM AUTHOR]

This paper attempts to isolate a literary image, a transsexual alien living among the squatter community in London as it appears in the novel Breve historia de la inmortalidad by Antonio Alamo, in order to trace the fluctuations that it can suffer once it is included in the global processes of identity construction and the dynamics of information that rule postmodernism from the mass media, inevitably mutating once it serves the hegemonic imaginary of consumption and the cultural mainstream which may shape it to illustrate different contents as a metaphor. [ABSTRACT FROM AUTHOR]

In this paper, I outline one strand in a genealogy of 'liveness', exploring the role of media in its emergence as a privileged spatio-temporal organization of experience. In order to consider the opportunities afforded by current developments in 'live methods' I then explore some of the implications for sociology of not simply studying practices of mediation but of inhabiting media, of being in medias res. Here I propose an amphibious sociology, for the potential it offers sociology to deploy methods reflexively in more than one medium, contrasting the methods of making distributive middles to the methods of establishing measures of representativeness, and exploring the opportunities and pitfalls of participation, or being in the middle. [ABSTRACT FROM AUTHOR]

Loïc Wacquant has made a widely read and debated contribution to critical research on contemporary urban marginality. A central part of the theoretical framework is that residents of deprived areas internalize territorial stigmatization, which then has a range of negative effects. Based on empirical research this paper assesses Wacquant's conception of territorial stigmatization and suggests some points where urban sociology might go beyond or adjust Wacquant. The empirical research focuses on Aalborg East, a deprived area in the northern part of Denmark. Through media analysis it is documented that Aalborg East is subject to territorial stigmatization, and it is suggested that cultural racism plays an important role. Qualitative interview data suggest, however, that the residents do not internalize or resign to the stigma. They become sad or angry when confronted with the stigma, but they have an either positive or ambivalent view of the area and most of them are content to live there. This finding is validated by survey data. Wacquant's conception cannot be entirely rejected, though, as the construction of internal dividing lines in some interviews can be interpreted as a way of managing territorial stigmatization. Nevertheless, the data provide little support for a theory of clear-cut internalization of territorial stigmatization in the case of Aalborg East. This conclusion leads to three discussions: a confirmation of Wacquant's claim that the role of the state matters; a discussion of the specific political culture of Scandinavian societies; and a problematization of Wacquant's reliance on Bourdieu's conception of symbolic violence. [ABSTRACT FROM AUTHOR]

New medicines represent exciting possibilities to individual patients for improved futures through reduced morbidity, as well as the potential for disappointment where promised outcomes are not forthcoming. For healthcare systems these technologies can enable enhanced effectiveness as well as spiralling costs, depending on value-for-money offered. Amidst uncertainty over efficacy and pricing, institutions such as the National Institute for Health and Clinical Excellence have been set up to regulate the cost-effectiveness of new products. The increased transparency of this new regulation, combined with inescapable uncertainties, leads to the heightened politicisation of decision-making and an insidious subjectivity beneath a veneer of rational-bureaucracy. This paper develops a theoretical framework for understanding the influence of hope within such contexts. Conceptualised here as ideological, affective and prone to lapsing into trust, hope is considered to shape the lifeworld-background of regulatory decisions and mask uncertainty around effectiveness. These processes challenge regulator legitimacy and effectiveness within polycentric regimes, through the distortion of communication and the manipulation of blame. [ABSTRACT FROM AUTHOR]

Since 2003, avian influenza has recently spread around the world sparking fears of a potential pandemic. As a result of this, a range of explanations and expectations surrounding the phenomenon were generated. Such social representations of disease depict the issue under discussion and frame reactions to the event. This paper explores the social representations surrounding avian influenza in Australia. Methodologically, a textual analysis of media and government documents was conducted in order to uncover the social representations implicit in these accounts. This demonstrated a symbolic framing of avian influenza with reference to the Spanish Influenza pandemic (1918). Analytically, the study draws upon the concepts of social representations from Durkheim and of risk and symbolic risk in the work of Beck. Overall, it is argued that the framing of avian influenza as a risk, mediated through the collective memory of Spanish Influenza, characterised the nature of the social representations surrounding the phenomenon. This resulted in the production of symbolic solutions to the threat. [ABSTRACT FROM AUTHOR]

This paper argues that a better articulated conception of stigma can enhance the analysis of popular culture. Beginning with the work on stigma by Erving Goffman and other scholars, the article contends that the stigma sometimes attached to the production and consumption of popular culture is distinct from the low status associated with certain forms of popular culture. Unlike low status, stigma discredits cultural forms and practitioners often rendering them problematic. This reassessment of stigma is applied and developed further through a study of comic books, showing the various ways stigma can operate in popular culture. The analysis suggests that stigma significantly impeded the evolution of the comic book as an art form, illustrating the potential negative effects of stigma in popular culture. [ABSTRACT FROM AUTHOR]

A distinctive dimension of political life, power as the capacity for people to act in concert, was a key in understanding one of the major transformations of the late twentieth century—the democratic aftermath of the collapse of the Soviet empire in central Europe. In this paper, the way this dimension—the politics of small things—provides alternatives in the United States is analyzed. A new media regime, with significant interactions between virtual and embodied social interactions, has opened up the opportunity for a new democratic politics. The antiwar movement and the Dean campaign are shown to have constituted alternative political possibilities for those critical of hegemonic discourses and practices. [ABSTRACT FROM AUTHOR]

This paper uses the work of Michel de Certeau (1988) to argue that it is possible to distinguish between "expert" or "authorised" approaches to media theory, construed as existing "strategically" within the "proper place" of the academy, and "tactical" appropriations of media theory operating in audience discourses. It takes media fan audiences as one case study in relation to this process, arguing that fans should be viewed as "poaching" from "official" media theory as well as from "official" media texts. It then goes on to suggest that we should not univocally celebrate or romanticise fans' uses of media theory, but should remain alert to the sociological and cultural reproductions that otherwise "tactical" media theory can participate in. This means rethinking fans' "tactics" not merely as the "arts of the weak" (de Certeau 1988, 37), but simultaneously as forms of appropriation that might enact forms of (sub)cultural power for fans. [ABSTRACT FROM AUTHOR]

Modern market-driven mass media systems may present collective actors with communication opportunities, but these come laced with formidable costs and constraints. This paper argues that despite these barriers, collective actors, working intentionally and strategically, can develop effective media campaigns to communicate with mass audiences – audiences they cannot reach directly. To utilize these narrow opportunities, however, a collective actor needs both adequate communications infrastructure and a communication strategy well integrated into its overall organizing strategy. The 1997 Teamsters strike against United Parcel Service (U.P.S.) provides an illustrative case. [ABSTRACT FROM AUTHOR]