Mobilizing the Trump Train: Understanding Collective Action in a Political Trolling Community

Political trolls initiate online discord not only for the lulz (laughs) but also for ideological reasons, such as promoting their desired political candidates. Political troll groups recently gained spotlight because they were considered central in helping Donald Trump win the 2016 US presidential election, which involved difficult mass mobilizations. Political trolls face unique challenges as they must build their own communities while simultaneously disrupting others. However, little is known about how political trolls mobilize sufficient participation to suddenly become problems for others. We performed a quantitative longitudinal analysis of more than 16 million comments from one of the most popular and disruptive political trolling communities, the subreddit /r/The\_Donald (T\D). We use T_D as a lens to understand participation and collective action within these deviant spaces. In specific, we first study the characteristics of the most active participants to uncover what might drive their sustained participation. Next, we investigate how these active individuals mobilize their community to action. Through our analysis, we uncover that the most active employed distinct discursive strategies to mobilize participation, and deployed technical tools like bots to create a shared identity and sustain engagement. We conclude by providing data-backed design implications for designers of civic media

THE LINGUISTIC CONSTRUCTION OF ASSOCIATIVE PERSONAL LABELIZATION OF FACEBOOKERS’ NICKS

This study investigates nicks (nicknames) of Facebook users (Facebookers). It specifically reveals the process of how Facebookers associate themselves with their nicknames and with all things around them. This study also finds out the factors that contribute to the choice of Facebookers to use their nicknames. This study uses sociolinguistic to approach the data. The data were obtained by using content analysis method. The data analysis method used to analyze the data was the Correlation Method with referents as the determining elements. The result of the study shows that there are personal identities associated to the nicknames used by Facebook users. It also shows that the uses of the nicknames by the Facebook users are influenced by their personal fancies (personal labelization). Besides, there are fifteen factors contributing to the choices of nicks (nicknames) by Facebook users, five major reasons that caused the informants to create the unique nicks and three issues which can be summarized related to personal autolabelization phenomena

Two cultures, one room: investigating language and gender in Kuwait

PhDKuwait is a gender-segregated country. Its conservative cultural ideology is evident in all areas of social life, including the way people communicate. Men and women have to make conscious language choices during everyday interaction. Certain aspects of Kuwaiti conversational registers are exclusive to either men or women, which reflects not only men’s and women’s separate socialization as children but also separate lifestyles as adults. Kuwait’s gendered context is therefore bound to be unique and of particular sociolinguistic interest, especially since mainstream language and gender literature has more often focused on English-speaking cultures. Thus, there is little knowledge of Arab gender-segregated cultures and this could possibly be due to complications that the researcher inevitably encounters when examining a sensitive issue such as gender within these constraints. The present research study investigates mixed interaction between Kuwaiti men and women in online chat rooms. In this particular online context, chat room users employ interactional strategies to negotiate the norms of heterosexual interaction which are often non-existent in offline Kuwaiti society. A combined framework of sociolinguistic, ethnographic methods is adopted to examine chat room interactional choices that enable men and women to construct gendered chat room identities as well as create a virtual online community of practice without undermining offline gender norms

User data discovery and aggregation: the CS-UDD algorithm

In the social web, people use social systems for sharing content and opinions, for communicating with friends, for tagging, etc. People usually have different accounts and different profiles on all of these systems. Several tools for user data aggregation and people search have been developed and protocols and standards for data portability have been defined. This paper presents an approach and an algorithm, named Cross-System User Data Discovery (CS-UDD), to retrieve and aggregate user data distributed on social websites. It is designed to crawl websites, retrieve profiles that may belong to the searched user, correlate them, aggregate the discovered data and return them to the searcher which may, for example, be an adaptive system. The user attributes retrieved, namely attribute-value pairs, are associated with a certainty factor that expresses the confidence that they are true for the searched user. To test the algorithm, we ran it on two popular social networks, MySpace and Flickr. The evaluation has demonstrated the ability of the CS-UDD algorithm to discover unknown user attributes and has revealed high precision of the discovered attributes

From Bonehead to @realDonaldTrump : A Review of Studies on Online Usernames

In many online services, we are identified by self-chosen usernames, also known as nicknames or pseudonyms. Usernames have been studied quite extensively within several academic disciplines, yet few existing literature reviews or meta-analyses provide a comprehensive picture of the name category. This article addresses this gap by thoroughly analyzing 103 research articles with usernames as their primary focus. Despite the great variety of approaches taken to investigate usernames, three main types of studies can be identified: (1) qualitative analyses examining username semantics, the motivations for name choices, and how the names are linked to the identities of the users; (2) experiments testing the communicative functions of usernames; and (3) computational studies analyzing large corpora of usernames to acquire information about the users and their behavior. The current review investigates the terminology, objectives, methods, data, results, and impact of these three study types in detail. Finally, research gaps and potential directions for future works are discussed. As this investigation will demonstrate, more research is needed to examine naming practices in social media, username-related online discrimination and harassment, and username usage in conversations.Peer reviewe

Computer-mediated knowledge communication

New communication technologies enable an array of new working and learning scenarios in which knowledge is being communicated. This article deals with the question to what extent these technologies can impede or facilitate knowledge communication. First, the various computer-based communication technologies will be classified. Second, effects of the medium on knowledge communication will be discussed based on results of studies of the current special priority program "Net-based Knowledge Communication in Groups". Third and last, computer-based possibilities to facilitate computer-mediated knowledge communication will be reviewNeue Kommunikationstechnologien ermöglichen eine Reihe neuer Arbeits- und Lernszenarien in denen Wissen kommuniziert wird. Dieser Beitrag beschäftigt sich damit, inwiefern diese Technologien Wissenskommunikation einschränken oder fördern können. Dazu werden in einem ersten Schritt die verschiedenen computerbasierten Kommunikationstechnologien untergliedert. In einem zweiten Schritt werden Wirkungen des Mediums auf die Wissenskommunikation diskutiert. Dazu werden u. a. die Ergebnisse von Studien des aktuellen Forschungsschwerpunkts "Netzbasierte Wissenskommunikation in Gruppen" berichtet. In einem dritten und letzten Schritt werden computerbasierte Möglichkeiten zusammengefasst, computervermittelte Wissenskommunikation zu förd

How fluidity drives the evolution of group norms in open online communities: A dialectical model

This paper develops a dialectic process model to explain how group norms evolve in self-organizing open online communities. Archive data collected from a celebrity fandom community is used for a netnography study that is complemented by an interview with the community administrator. The analysis of the data reveals that the fluidity of online communities triggers changes on norm conformity leading to increased peer to peer moderations. That raised contradictions on norm schema (clarity and alignment with the community identity). I find drivers that affect the resolution of norm contradictions. This paper develops an iterative model to explain how norm contradictions are continuously raised due to fluidity and resolved by community members. The findings have theoretical and practical implication on the sustainability and fluidity of online communities from group norm perspective

Analyzing the Language of Food on Social Media

We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and demonstrate that many latent population characteristics can be directly predicted from this data: overweight rate, diabetes rate, political leaning, and home geographical location of authors. For all tasks, our language-based models significantly outperform the majority-class baselines. Performance is further improved with more complex natural language processing, such as topic modeling. We analyze which textual features have most predictive power for these datasets, providing insight into the connections between the language of food, geographic locale, and community characteristics. Lastly, we design and implement an online system for real-time query and visualization of the dataset. Visualization tools, such as geo-referenced heatmaps, semantics-preserving wordclouds and temporal histograms, allow us to discover more complex, global patterns mirrored in the language of food.Comment: An extended abstract of this paper will appear in IEEE Big Data 201

Lavender Linguistics & HIV Discourse: How Do Gay AIDS Generation and Millennial Men Talk About HIV?

William Leap coined the term lavender linguistics in the early 1990’s. The expression refers to linguistic features unique to the LGBT (Lesbian, Gay, Bisexual, Transgender) community. Lavender linguistics (Leap, 1995) in HIV discourse is no exception. Although few studies exist in lavender linguistics and HIV discourse, a broad spectrum on this topic has been gained from these studies. Topics in the language marked specifically by LGBT speakers in HIV discourse include racial/ ethnic backgrounds, blood, art and entertainment, activism, camp humor, sex, drugs, online language, HIV treatment, and HIV prevention. Applying lavender linguistics in general, Communities of Practice (Wenger, 1998), AIDSpeak, and HIV history provide a glimpse of how lavender linguistics and HIV discourse has developed to how it is shaped today. Additionally, using interview and focus group data as a lens provided an idea of how the AIDS Generation and Millennial gay men differ in their HIV discourse. This qualitative study used interviews and focus groups to collect data. Participants were placed in two groups: AIDS Generation (participants were born between 1952-1973) and Millennials (participants were born between 1989-1996). There were 12 AIDS Generation and 11 Millennial participants involved who were found in a metropolitan area in the Upper Midwest. This study examined common choice in words, idioms/ figures of speech, multiple word expressions, and phrases and how they reflect on their HIV-related experiences and beliefs. The data collection was placed in four themes: HIV, Stigma, Sex, and Drugs. The analysis process found numerous similarities and differences in how the two generations discuss HIV. These similarities and differences imply how their experiences related to HIV shapes their language features