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In the last few years, especially after the Brexit referendum and the 2016 U.S. elections, there has been a surge in academic interest for misinformation and disinformation. Social, cognitive, and political scientists' work on these phenomena has focused on two main aspects: Individuals' (and by extension societies') vulnerability to misinformation;Factors and interventions that can increase individuals' (and societies') resistance to misinformation. In this article, we offer a critical review of the psychological research pertaining to these two aspects. Drawing on this review, we highlight an emerging tension in the relevant literature. Indeed, the current state of the art of the political misinformation literature reflects the combined operation of two opposing psychological constructs: excess gullibility on the one hand and excess vigilance on the other. We argue that this conceptualization is important in both advancing theories of individuals' and societies' vulnerability to misinformation and in designing prospective research programs. We conclude with proposing what, in our view, are the most promising avenues for future research in the field. [ABSTRACT FROM AUTHOR]

Recent election surprises, regime changes, and political shocks indicate that political agendas have become more fast-moving and volatile. The ability to measure the complex dynamics of agenda change and capture the nature and extent of volatility in political systems is therefore more crucial than ever before. This study proposes a definition and operationalization of volatility that combines insights from political science, communications, information theory, and computational techniques. The proposed measures of fractionalization and agenda change encompass the shifting salience of issues in the agenda as a whole and allow the study of agendas across different domains. We evaluate these metrics and compare them to other measures such as issue-level survival rates and the Pedersen Index, which uses public-opinion poll data to measure public agendas, as well as traditional media content to measure media agendas in the UK and Germany. We show how these measures complement existing approaches and could be employed in future agenda-setting research. [ABSTRACT FROM AUTHOR]

Political campaigning on social media is a core feature of contemporary democracy. However, evidence of the effectiveness of this type of campaigning is thin. This study tests three theories linking social media to vote outcomes, using a novel 6,000 observation panel data set from two British elections. We find that Twitter-based campaigning does seem to help win votes. The impact of Twitter use is small, though comparable with campaign spending. Our data suggest that social media campaign effects are achieved through using Twitter as a broadcast mechanism. Despite much literature encouraging politicians to engage with social platforms in an interactive fashion, we find no evidence that this style of communication improves electoral outcomes. In light of our results, theories of how social media are changing processes of campaigns and elections are discussed and enhanced. [ABSTRACT FROM AUTHOR]

Social media has become an emerging alternative to opinion polls for public opinion collection, while it is still posing many challenges as a passive data source, such as structurelessness, quantifiability, and representativeness. Social media data with geotags provide new opportunities to unveil the geographic locations of users expressing their opinions. This paper aims to answer two questions: 1) whether quantifiable measurement of public opinion can be obtained from social media and 2) whether it can produce better or complementary measures compared to opinion polls. This research proposes a novel approach to measure the relative opinion of Twitter users towards public issues in order to accommodate more complex opinion structures and take advantage of the geography pertaining to the public issues. To ensure that this new measure is technically feasible, a modeling framework is developed including building a training dataset by adopting a state-of-the-art approach and devising a new deep learning method called Opinion-Oriented Word Embedding. With a case study of tweets on the 2016 U.S. presidential election, we demonstrate the predictive superiority of our relative opinion approach and we show how it can aid visual analytics and support opinion predictions. Although the relative opinion measure is proved to be more robust than polling, our study also suggests that the former can advantageously complement the latter in opinion prediction. [ABSTRACT FROM AUTHOR]

Cultural organizations are categorized by cultural products (high or popular culture) and by organizational form (nonprofit or commercial). In sociology, these classifications are understood predominantly through a Bourdieusian lens, which links cultural consumption to habitus and a class-based struggle for distinction. However, people’s engagement with institutionalized cultural classifications may be expressed differently on the Internet, where a culture of hierarchy-free equality is (sometimes) idealized. Using digital trace data from a representative sample of 280 user-generated reviews of four London cultural organizations, we find that reviewers are concerned with practical issues over cultural content, displaying a popular orientation to cultural consumption (an “audience-focus” or an “embodied” approach). A very small minority of reviewers claim status honor on a variety of bases, including symbolic mastery of traditional cultural capital. Overall, we find an online space in the cultural sphere in which cultural hierarchies are not relevant. [ABSTRACT FROM AUTHOR]

Political behaviour increasingly takes place on digital platforms, where people are presented with a range of social information—real-time feedback about the behaviour of peers and reference groups—which can stimulate (or depress) participation. This social information is hypothesized to impact the distribution of political activity, stimulating participation in mobilizations that are increasing in popularity, and depressing participation in those that appear to be less popular, leading to a non-normal distribution. Changes to these platforms can generate natural experiments allowing for an estimate of the impact of different kinds of social information on participation. This paper tests the hypothesis that social information shapes the distribution of political mobilizations by examining the introduction of trending information to the homepage of the UK government petition platform. The introduction of the trending feature did not increase the overall number of signatures per day, but the distribution of signatures across petitions changed significantly—the most popular petitions gained more signatures at the expense of those with fewer signatories. We further find significant differences between petitions trending at different ranks on the homepage. This evidence suggests that the ubiquity of trending information on digital platforms is introducing instability into political markets, as has been shown for cultural markets. As well as highlighting the importance of digital design in shaping political behaviour, the findings suggest that a non-negligible group of individuals visit the homepage of the site looking for petitions to sign, without having decided the issues they wish to support in advance. These ‘aimless petitioners’ are particularly susceptible to changes in social information. [ABSTRACT FROM AUTHOR]

The digital revolution has affected museums in many ways, both directly and indirectly. A major external change is the rise of user‐written reviews; that is, reviews written by museum visitors and posted on the Internet. User‐generated reviews pose challenges to museums, as they are publicly available and largely outside the control of museums. This article discusses research on reviews of accredited museums in London. Our data set consists of all reviews written about 88 London museums that were posted on TripAdvisor during 2014, a total of 22,940 reviews. Using a technique called topic modelling, we describe 19 themes in reviewers' stories of their visits. We find that museum visitors pay attention to the ancillary aspects of their visit: queues, cost, food service, toilets, and activities for children. They make fewer comments on the cultural side of the museum experience. However, these cultural aspects do matter and are associated with positive reviews. We argue that reviewers consider museums as part of a wider leisure sector. The article concludes with a discussion of the implications of our study for museum management and assess the usefulness of user‐generated content as a source of data on museum visitors. [ABSTRACT FROM AUTHOR]

We investigate the causal uncertainty surrounding the flash crash in the U.S. Treasury bond market on October 15, 2014, and the unresolved concern that no clear link has been identified between the start of the flash crash at 9:33 and the opening of the U.S. equity market at 9:30. We consider the contributory effect of mini flash crashes in equity markets, and find that the number of equity mini flash crashes in the three-minute window between market open and the Treasury Flash Crash was 2.6 times larger than the number experienced in any other three-minute window in the prior ten weekdays. We argue that (a) this statistically significant finding suggests that mini flash crashes in equity markets both predicted and contributed to the October 2014 U.S. Treasury Bond Flash Crash, and (b) mini-flash crashes are important phenomena with negative externalities that deserve much greater scholarly attention. [ABSTRACT FROM AUTHOR]

The emergence of large stores of transactional data generated by increasing use of digital devices presents a huge opportunity for policymakers to improve their knowledge of the local environment and thus make more informed and better decisions. A research frontier is hence emerging which involves exploring the type of measures that can be drawn from data stores such as mobile phone logs, Internet searches and contributions to social media platforms and the extent to which these measures are accurate reflections of the wider population. This paper contributes to this research frontier, by exploring the extent to which local commuting patterns can be estimated from data drawn from Twitter. It makes three contributions in particular. First, it shows that heuristics applied to geolocated Twitter data offer a good proxy for local commuting patterns; one which outperforms the current best method for estimating these patterns (the radiation model). This finding is of particular significance because we make use of relatively coarse geolocation data (at the city level) and use simple heuristics based on frequency counts. Second, it investigates sources of error in the proxy measure, showing that the model performs better on short trips with higher volumes of commuters; it also looks at demographic biases but finds that, surprisingly, measurements are not significantly affected by the fact that the demographic makeup of Twitter users differs significantly from the population as a whole. Finally, it looks at potential ways of going beyond simple frequency heuristics by incorporating temporal information into models. [ABSTRACT FROM AUTHOR]

Tile maps are an important tool in thematic cartography with distinct qualities (and limitations) that distinguish them from better-known techniques such as choropleths, cartograms and symbol maps. Specifically, tile maps display geographic regions as a grid of identical tiles so large regions do not dominate the viewer's attention and small regions are easily seen. Furthermore, complex data such as time series can be shown on each tile in a consistent format, and the grid layout facilitates comparisons across tiles. Whilst a small number of handcrafted tile maps have become popular, the time-consuming process of creating new tile maps limits their wider use. To address this issue, we present an algorithm that generates a tile map of the specified type (e.g. square, hexagon, triangle) from raw shape data. Since the 'best' tile map depends on the specific geography visualized and the task to be performed, the algorithm generates and ranks multiple tile maps and allows the user to choose the most appropriate. The approach is demonstrated on a range of examples using a prototype browser-based application. [ABSTRACT FROM AUTHOR]

Multilingualism is common offline, but we have a more limited understanding of the ways multilingualism is displayed online and the roles that multilinguals play in the spread of content between speakers of different languages. We take a computational approach to studying multilingualism using one of the largest user-generated content platforms, Wikipedia. We study multilingualism by collecting and analyzing a large dataset of the content written by multilingual editors of the English, German, and Spanish editions of Wikipedia. This dataset contains over two million paragraphs edited by over 15,000 multilingual users from July 8 to August 9, 2013. We analyze these multilingual editors in terms of their engagement, interests, and language proficiency in their primary and non-primary (secondary) languages and find that the English edition of Wikipedia displays different dynamics from the Spanish and German editions. Users primarily editing the Spanish and German editions make more complex edits than users who edit these editions as a second language. In contrast, users editing the English edition as a second language make edits that are just as complex as the edits by users who primarily edit the English edition. In this way, English serves a special role bringing together content written by multilinguals from many language editions. Nonetheless, language remains a formidable hurdle to the spread of content: we find evidence for a complexity barrier whereby editors are less likely to edit complex content in a second language. In addition, we find that multilinguals are less engaged and show lower levels of language proficiency in their second languages. We also examine the topical interests of multilingual editors and find that there is no significant difference between primary and non-primary editors in each language. [ABSTRACT FROM AUTHOR]

The internet has been ascribed a prominent role in collective action, particularly with widespread use of social media. But most mobilisations fail. We investigate the characteristics of those few mobilisations that succeed and hypothesise that the presence of 'starters' with low thresholds for joining will determine whether a mobilisation achieves success, as suggested by threshold models. We use experimental data from public good games to identify personality types associated with willingness to start in collective action. We find a significant association between both extraversion and internal locus of control, and willingness to start, while agreeableness is associated with a tendency to follow. Rounds without at least a minimum level of extraversion among the participants are unlikely to be funded, providing some support for the hypothesis. [ABSTRACT FROM AUTHOR]

The movements of ideas and content between locations and languages are unquestionably crucial concerns to researchers of the information age, and Twitter has emerged as a central, global platform on which hundreds of millions of people share knowledge and information. A variety of research has attempted to harvest locational and linguistic metadata from tweets to understand important questions related to the 300 million tweets that flow through the platform each day. Much of this work is carried out with only limited understandings of how best to work with the spatial and linguistic contexts in which the information was produced, however. Furthermore, standard, well-accepted practices have yet to emerge. As such, this article studies the reliability of key methods used to determine language and location of content in Twitter. It compares three automated language identification packages to Twitter's user interface language setting and to a human coding of languages to identify common sources of disagreement. The article also demonstrates that in many cases user-entered profile locations differ from the physical locations from which users are actually tweeting. As such, these open-ended, user-generated profile locations cannot be used as useful proxies for the physical locations from which information is published to Twitter. [ABSTRACT FROM AUTHOR]

This research analyzes linguistic barriers and cross-lingual interaction through link analysis of more than 100,000 blogs discussing the 2010 Haitian earthquake in English, Spanish, and Japanese. In addition, cross-lingual hyperlinks are qualitatively coded. This study finds English-language blogs are significantly less likely to link cross-lingually than Spanish or Japanese blogs. However, bloggers' awareness of foreign language content increases over time. Personal blogs contain most cross-lingual links, and these links point to (primarily English-language) media. Finally, most cross-lingual links in the dataset signal a citation or reference relationship while a smaller number of cross-lingual links signal a translation. Although most bloggers link to other blogs in the same language, the dataset reveals a surprising level of human translation in the blogosphere. [ABSTRACT FROM AUTHOR]

A random-effects meta-analysis of research concerning the door-in-the-face (DITF) influence strategy provides evidence supporting more confident generalizations about the role of several moderator variables than that provided by previous reviews. Variations in the identity of the requester, the identity of the beneficiary, the prosocialness of the requests, the medium of communication, and the time interval between requests all appear to influence the size of DITF effects; variations in concession size do not. DITF effects are small in absolute terms (with an overall mean r of .10), but not remarkably small in the context of other effect sizes concerning social influence. However, there is substantial variability in DITF effects, even under optimal conditions. The review's findings are not easily reconciled with most proposed explanations of DITF effects, but appear consistent with a guilt-based account. [ABSTRACT FROM AUTHOR]

• Study focused on influenza vaccination avoidant 18-49-year-old adults. • Experiment examined whether supplemental flu vaccine education materials helped. • Immersive VR showed promise when it generated a sense of presence. • Presence was associated with positive outcomes on beliefs and intentions. • VR holds promise for communicating key immunization concepts. Only one-third of adults 18–49 years old in the United States receive a recommended annual influenza vaccination. This study examined whether supplementing vaccine information statements (VIS) with an immersive virtual reality (VR), short video or electronic pamphlet story designed to convey the community immunity benefits of influenza vaccination would improve influenza vaccine avoidant participants' influenza-related perceptions as well as their influenza vaccination-related beliefs, confidence and intentions. A one-way between-subjects experimental design compared the effects of adding a supplemental education experience prior to VIS exposure with flu vaccine avoidant 18-to-49-year-olds. The 171 participants recruited from the community were randomly assigned to one of three modality treatment conditions [VR, video, or e-pamphlet (i.e., story board presented via electronic tablet)] or a VIS-only control condition. Compared to the modalities, the VR intervention created a stronger perception of presence (i.e., feeling of "being there" in the story), which, in turn, increased participants' concern about transmitting influenza to others and raised vaccination intention. Increased concern about transmitting influenza to others was associated with positive effects on influenza vaccination-related beliefs, including confidence that one's flu vaccination would protect others. Neither the e-pamphlet nor the video intervention were able to elicit a sense of presence nor were they able to improve the impact of the VIS on the outcome measures. Immersive VR has much potential to increase understanding of key immunization concepts, such as community immunity, through creative executions that increase a sense of presence. Given the need to increase influenza vaccination uptake among 18-to-49-year-olds, and the projected growth in VR accessibility and use, additional applications and assessments related to vaccination communication and education are needed and warranted. By increasing the ability to convey key vaccine and immunization concepts, immersive VR could help address vaccination hesitancy and acceptance challenges. [ABSTRACT FROM AUTHOR]

Accurate modelling of local population movement patterns is a core, contemporary concern for urban policymakers, affecting both the short-term deployment of public transport resources and the longer-term planning of transport infrastructure. Yet, while macro-level population movement models (such as the gravity and radiation models) are well developed, micro-level alternatives are in much shorter supply, with most macro-models known to perform poorly at smaller geographical scales. In this paper, we take a first step to remedy this deficit, by leveraging two novel datasets to analyse where and why macro-level models of human mobility break down. We show how freely available data from OpenStreetMap concerning land use composition of different areas around the county of Oxfordshire in the UK can be used to diagnose mobility models and understand the types of trips they over- and underestimate when compared with empirical volumes derived from aggregated, anonymous smartphone location data. We argue for new modelling strategies that move beyond rough heuristics such as distance and population towards a detailed, granular understanding of the opportunities presented in different regions., Competing Interests: The authors declare no competing financial interests., (© 2019 The Authors.)

Seafood processing often removes morphological properties of seafood species that enable the consumer to distinguish one type of organism from another. For this reason, species substitution is the most common form of economic adulteration in the seafood industry. Visible and near-infrared spectroscopy (Vis/NIR) has been used to detect and quantify species authenticity and adulteration in crabmeat samples. Atlantic blue crabmeat was adulterated with blue swimmer crabmeat in 10% increments. Water absorption bands dominated the main features in the crabmeat spectra, with a decrease in sample absorbance with increasing adulteration percentage. Several data pretreatments, i.e., moving average, combing, first and second derivatives, and multiplicative scatter correction, in addition to the raw data, were investigated for prediction and quantitative data analysis using partial least-squares. In addition, quantitative analysis was done using the full spectrum and a sequential approach in which 50 wavelengths were added sequentially to determine a new model and find an optimal solution. The results suggest that Vis/NIR spectroscopy is a suitable technology that can be applied to detect and quantify species authenticity and adulteration in crabmeat.