Modeling the adoption and use of social media by nonprofit organizations

This study examines what drives organizational adoption and use of social media through a model built around four key factors - strategy, capacity, governance, and environment. Using Twitter, Facebook, and other data on 100 large US nonprofit organizations, the model is employed to examine the determinants of three key facets of social media utilization: 1) adoption, 2) frequency of use, and 3) dialogue. We find that organizational strategies, capacities, governance features, and external pressures all play a part in these social media adoption and utilization outcomes. Through its integrated, multi-disciplinary theoretical perspective, this study thus helps foster understanding of which types of organizations are able and willing to adopt and juggle multiple social media accounts, to use those accounts to communicate more frequently with their external publics, and to build relationships with those publics through the sending of dialogic messages.Comment: Seungahn Nah and Gregory D. Saxton. (in press). Modeling the adoption and use of social media by nonprofit organizations. New Media & Society, forthcomin

The Role of Language in the Media in Influencing Public Perceptions of Refugees

The refugee crisis has become a worldwide epidemic in recent years. As refugee entrance into host countries is debated, media outlets are covering the issue regularly. These media outlets use various types of language when portraying refugees. Many publications have been found to convey hostile and divisive themes as well as use specific linguistic tools, which contribute to negative portrayals of refugees. Media outlets have the potential to influence public perceptions of refugees because the general public in a host country receives its information primarily from the media. Overt and subtle language used to describe refugees has been previously found to influence public opinions. This study of 101 students at a conservative Christian university in the mid-Atlantic United States was designed to examine whether manipulated language in news articles impacted perceptions of refugees. Participants were randomly assigned to the positive or negative language condition and then asked to complete a survey assessing four facets of perception. None of the results were significant, indicating the language in the article did not impact perceptions of refugees. This study was limited by lack of diversity in the sample, the use of self-report data, potential personal confounds, and a small sample size. The results implied a need for balance when calling for media ethics and a need for many more empirical studies in this area

Anticipating new media: A faceted classification of material types

The emergence of new media types, many seemingly without counterparts in the non-digital world, challenges the readiness of existing knowledge organization schemes to accommodate them. A knowledge organization scheme based on a faceted analysis of existing classes of bibliographic materials is likely to accommodate new developments better than one based on a list of unanalyzed material types. The faceted analysis undertaken here, in which seven facets are recognized (content, generation of content, recording of content, publication/distribution, physical characteristics, perception/use, and relationships) shows the inadequacy of the traditional view of the bibliographic community of a fundamental distinction between content and carrier; interaction between content and carrier is common and enters into the characterization of material types. The facet analysis is validated by applying it to two new material types, wikis and blogs

Human-AI Collaboration in Content Moderation: The Effects of Information Cues and Time Constraints

An extremely large amount of user-generated content is produced by users worldwide every day with the rapid development of online social media. Content moderation has emerged to ensure the quality of posts on various social media platforms. This process typically demands collaboration between humans and AI because of the complementarity of the two agents in different facets. Wondering how AI can better assist humans to make final judgment in the “machine-in-the-loop” paradigm, we propose a lab experiment to explore the influence of different types of cues provided by AI through a nudging approach as well as time constraints on human moderators’ performance. The proposed study contributes to the literature on the AI-assisted decision-making pattern, and helps social media platforms in creating an effective human-AI collaboration framework for content moderation

Test item taxonomy based of functional criteria

There are many taxonomies that try to classify and apply some consistency to the very many item types currently in existence. They all have various limitations, however, such as ambiguous classification criteria, little discrimination between format types, and referring almost exclusively to pen-and-paper or screen-based items. This paper aims to overcome these limitations by proposing a new item format taxonomy based on functional criteria. Current classifications are reviewed, the criteria they are based on are examined and their limitations are identified. The proposed alternative classification identifies four essential components of items according to function: the structure of the included content, the device used for transmission of the question to the examinee, the device for receiving the response, and the instructions to the examinee about how to understand and respond to the item. The combination of different facets of these four components allows any format of item to be classified, both existing formats and those that may appear in the future. In addition to systematically and coherently classifying items, this new taxonomy may also be of great utility in the construction and research of new items. The proposed model is illustrated by examples showing how specific items are classified, using a checklist as a guide.Ministerio de Economía y Competitividad de España PSI2014-56114-PMinisterio de Economía y Competitividad de España PSI2017-85724-

Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling

Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques. Findings of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems. However, not only analytical visualizations may be too complex for target audience but also the information that needs to be presented. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, which involves two aspects: information and display complexity. We propose a general framework where data analysis and result presentation are linked by story synthesis, in which the analyst creates and organizes story contents. Differently, from the previous research, where analytic findings are represented by stored display states, we treat findings as data constructs. In story synthesis, findings are selected, assembled, and arranged in views using meaningful layouts that take into account the structure of information and inherent properties of its components. We propose a workflow for applying the proposed framework in designing visual analytics systems and demonstrate the generality of the approach by applying it to two domains, social media, and movement analysis

Interfacial depinning transitions in disordered media: revisiting an old puzzle

Interfaces advancing through random media represent a number of different problems in physics, biology and other disciplines. Here, we study the pinning/depinning transition of the prototypical non-equilibrium interfacial model, i.e. the Kardar-Parisi-Zhang equation, advancing in a disordered medium. We analyze separately the cases of positive and negative non-linearity coefficients, which are believed to exhibit qualitatively different behavior: the positive case shows a continuous transition that can be related to directed-percolation-depinning while in the negative case there is a discontinuous transition and faceted interfaces appear. Some studies have argued from different perspectives that both cases share the same universal behavior. Here, by using a number of computational and scaling techniques we shed light on this puzzling situation and conclude that the two cases are intrinsically different.Comment: 13 pages, 9 figure

Solutions to Detect and Analyze Online Radicalization : A Survey

Online Radicalization (also called Cyber-Terrorism or Extremism or Cyber-Racism or Cyber- Hate) is widespread and has become a major and growing concern to the society, governments and law enforcement agencies around the world. Research shows that various platforms on the Internet (low barrier to publish content, allows anonymity, provides exposure to millions of users and a potential of a very quick and widespread diffusion of message) such as YouTube (a popular video sharing website), Twitter (an online micro-blogging service), Facebook (a popular social networking website), online discussion forums and blogosphere are being misused for malicious intent. Such platforms are being used to form hate groups, racist communities, spread extremist agenda, incite anger or violence, promote radicalization, recruit members and create virtual organi- zations and communities. Automatic detection of online radicalization is a technically challenging problem because of the vast amount of the data, unstructured and noisy user-generated content, dynamically changing content and adversary behavior. There are several solutions proposed in the literature aiming to combat and counter cyber-hate and cyber-extremism. In this survey, we review solutions to detect and analyze online radicalization. We review 40 papers published at 12 venues from June 2003 to November 2011. We present a novel classification scheme to classify these papers. We analyze these techniques, perform trend analysis, discuss limitations of existing techniques and find out research gaps

New Formats, New Methods: Computational Approaches as a Way Forward for Media Entertainment Research

The rise of new technologies and platforms, such as mobile devices and streaming services, has substantially changed the media entertainment landscape and continues to do so. Since its subject of study is changing constantly and rapidly, research on media entertainment has to be quick to adapt. This need to quickly react and adapt not only relates to the questions researchers need to ask but also to the methods they need to employ to answer those questions. Over the last few years, the field of computational social science has been developing and using methods for the collection and analysis of data that can be used to study the use, content, and effects of entertainment media. These methods provide ample opportunities for this area of research and can help in overcoming some of the limitations of self-report data and manual content analyses that most of the research on media entertainment is based on. However, they also have their own set of challenges that researchers need to be aware of and address to make (full) use of them. This thematic issue brings together studies employing computational methods to investigate different types and facets of media entertainment. These studies cover a wide range of entertainment media, data types, and analysis methods, and clearly highlight the potential of computational approaches to media entertainment research. At the same time, the articles also include a critical perspective, openly discuss the challenges and limitations of computational methods, and provide useful suggestions for moving this nascent field forward