Wikipedia Talk Pages Research Articles

Jürgen Habermas revisited via Tim Cook's Wikipedia biography: A hermeneutic approach to critical Information Systems research

Critical Information Systems (IS) research is sometimes appreciated for the shades of gray it adds to sunny portraits of technology's emancipatory potential. In this article, we revisit a theory about Wikipedia’s putative freedom from the authority of corporate media's editors and authors. We present the curious example of Tim Cook's Wikipedia biography and its history of crowd-sourced editorial decisions, published on Wikipedia's talk pages. We use a hermeneutic method to subject the theory about Wikipedia's “rational discourse” and “emancipatory potential” to a soft, empirical test. When we examined Cook's Wikipedia biography and its editorial decisions, what we found pertained to authoritative discourse – the opposite of “rational discourse” – as well as Jürgen Habermas's concept of dramaturgical action. Our discussion aims to change how critical scholars think about IS's Habermasian theories and emancipatory technology. Our contribution – a critical intervention – is a clear alternative to mainstream IS research's moral prescriptions and mechanistic causes.

Proactive Moderation of Online Discussions: Existing Practices and the Potential for Algorithmic Support

To address the widespread problem of uncivil behavior, many online discussion platforms employ human moderators to take action against objectionable content, such as removing it or placing sanctions on its authors. Thisreactive paradigm of taking action against already-posted antisocial content is currently the most common form of moderation, and has accordingly underpinned many recent efforts at introducing automation into the moderation process. Comparatively less work has been done to understand other moderation paradigms---such as proactively discouraging the emergence of antisocial behavior rather than reacting to it---and the role algorithmic support can play in these paradigms. In this work, we investigate such a proactive framework for moderation in a case study of a collaborative setting: Wikipedia Talk Pages. We employ a mixed methods approach, combining qualitative and design components for a holistic analysis. Through interviews with moderators, we find that despite a lack of technical and social support, moderators already engage in a number of proactive moderation behaviors, such as preemptively intervening in conversations to keep them on track. Further, we explore how automation could assist with this existing proactive moderation workflow by building a prototype tool, presenting it to moderators, and examining how the assistance it provides might fit into their workflow. The resulting feedback uncovers both strengths and drawbacks of the prototype tool and suggests concrete steps towards further developing such assisting technology so it can most effectively support moderators in their existing proactive moderation workflow.

A Lightly Supervised Approach to Role Identification in Wikipedia Talk Page Discussions

In this paper we describe an application of a lightly supervised Role Identification Model (RIM) to the analysis of coordination in Wikipedia talk page discussions. Our goal is to understand the substance of important coordination roles that predict quality of the Wikipedia pages where the discussions take place. Using the model as a lens, we present an analysis of four important coordination roles identified using the model, including Workers, Critiquers, Encouragers, and Managers.

Verbal and multimodal metaphorical patterns in Wikipedia migration discourse

The use of metaphors in the refugee discourse since 2015 has so far mostly been explored in newspapers in different EU countries. In this study, we combine linguistic discourse metaphor analysis with a corpus-based approach, complementing qualitative and quantitative corpus evidence from Wikipedia migration corpus to explore verbal and multimodal metaphorical patterns. As a multimodal and multilingual hypertext, Wikipedia, represents a highly relevant source of information and a unique source for the multimodal and cross-linguistic discourse linguistic analysis. In this paper metaphorical expressions are considered as a transtextual discursive phenomenon in the light of Foucaudian tradition. The results of the study show that the analyzed migration discourse in Wikipedia is like the newspaper migration discourse predominantly structured by metaphorical patterns that draw from the source domains water flow/natural catastrophes as well as military/warfare. These source domains are conventionally used in relation to a wide range of target domains (multivalency), however, they play a constitutive role in the analyzed discourse by providing a specific view of events and emphasizing certain aspects and evaluations. The patterning of water flow metaphors across Wikipedia articles and talk pages is in multimodal metaphors extended, elaborated and reinforced in visual mode, referring to those migrating as a flow, wave, influx. However, especially on Wikipedia talk pages Wikipedians point to the dehumanization of those fleeing and the securitization of migration through metaphorical expressions as a problematic linguistic discourse practice

Participation and deliberative discourse on social media – Wikipedia talk pages as transnational public spheres?

ABSTRACT This paper focuses on the potential societal function of Wikipedia beyond serving as an encyclopedia. That is, it assesses both theoretically and empirically whether talk pages (TP) – Wikipedia discussion sites that accompany the encyclopedic entries and provide spaces for debates among Wikipedia editors – may function as transnational public spheres. Despite the increasing number of studies on citizen engagement and participation in the age of social media, Wikipedia as an example of the participatory internet has received little research attention in this regard. This study redresses this research gap in two steps. Drawing on Habermas’ concept of the public sphere and Fraser's and Eriksen's modifications thereof, Wikipedia's – specifically the TPs’ – modus operandi is explored to evaluate whether TPs may serve as spaces for transnational political opinion formation. This theoretical exploration is complemented with an empirical assessment of a TP dedicated to the EU. The case study addresses if/to what degree Wikipedia editors have appropriated the TP to function as a transnational public sphere. Findings indicate that Wikipedia TPs can – and do – serve as general transnational public spheres.

Toxic Comments Classification using Neural Network

Humans have built broad models of expressing their thoughts via several appliances. The internet has not only become a credible method for expressing one's thoughts, but is also rapidly becoming the single largest means of doing so. In this context, one area of focus is the study of negative online behaviors of users like, toxic comments that are threat, obscenity, insults and abuse. The task of identifying and removing toxic communication from public forums is critical. The undertaking of analyzing a large corpus of comments is infeasible for human moderators. Our approach is to use Natural Language Processing (NLP) techniques to provide an efficient and accurate tool to detect online toxicity. We apply TF-IDF feature extraction technique, Neural Network models to tackle a toxic comment classification problem with a labeled dataset from Wikipedia Talk Page.

“Wikipedia does NOT tolerate your babbling!”: Impoliteness-induced conflict (resolution) in a polylogal collaborative online community of practice

Impoliteness (and responding to it) is salient in various emerging cooperative, polylogal online communities of practice. Investigating Wikipedians' negotiations quantitatively and qualitatively, the researchers analyzed discussions in 120 highly controversial Wikipedia talk pages across four general topical categories to explore impoliteness strategies, their responses, and participation patterns characterizing conflict creation, escalation, and resolution in Wikipedians' polylogues. Both macro-analysis (i.e. number of participants, conflicts, turns across conflicts, and discoursal roles) and micro-analysis (impoliteness strategies and responses to them) along with pertinent frameworks (e.g. taxonomies of impoliteness strategies, defensive strategies, and participant response options and patterns) were utilized in analyzing the data. Findings emphasized the existence of impoliteness phenomena, the prevalence of on-record impoliteness strategies rather than off-record strategies, dominance of the defensive strategy of offering an explanation, as well as a tendency among all the participants (i.e. initiators, recipients, and witnesses) to resolve conflicts. The findings are discussed in light of the asynchronous, task-oriented, interaction-focused, polylogal, natively digital and highly-policed nature of the platform's communications. Offering a revised model of online conflict (resolution) interaction patterns, this research sheds new light on the communicative behaviors, norms and strategies of Wikipedians, as a distinct online community of practice with implications for technology-mediated incivility.

Types and annotation of reply relations in computer-mediated communication

AbstractThis paper presents types and annotation layers of reply relations in computer- mediated communication (CMC). Reply relations hold between post units in CMC interactions and describe references from one given post to a previous post. We classify three types of reply relations in CMC interactions: first, technical replies, i. e. the possibility to reply directly to a previous post by clicking a ‘reply’ button; second, indentations, e. g. in wiki talk pages in which users insert their contributions in the existing talk page by indenting them and third, interpretative reply relations, i. e. the reply action is not realised formally but signalled by other structural or linguistics means such as address markers ‘@’, greetings, citations and/or Q-A structures. We take a look at existing practices in the description and representation of such relations in corpora and examples of chat, Wikipedia talk pages, Twitter and blogs. We then provide an annotation proposal that combines the different levels of description and representation of reply relations and which adheres to the schemas and practices for encoding CMC corpus documents within the TEI framework as defined by the TEI CMC SIG. It constitutes a prerequisite for correctly identifying higher levels of interactional relations such as dialogue acts or discussion trees.

Canon wars: A semiotic and ethnographic study of a Wikipedia talk page debate concerning the canon of Star Wars

This article examines how Wikipedia editors who are also members of fan communities attempt to assemble articles on the ‘canon’ (i.e. the aspects of a fictional universe that are held as official by fans) of media objects of interest. Derived largely from an ethnographic study and semiotic analysis of the Wikipedia article ‘Star Wars canon’ and its accompanying ‘talk page’, this article argues the following: first, an article’s talk page often serves as its ‘heteroglossic preconscious’, functioning as a space in which fan editors can debate conflicting versions of canon. Once a definition is agreed on, the article itself is edited to reflect the consensus, and in the process becomes a monoglossic representation of the ‘One True Canon’ in the eyes of Wikipedia fan editors. Second, authority plays a major role in the creation of articles on canon, with the sayings of the author (who is often seen in the light of a quasi-deity) being revered. Authority, however, can be shared and even subsumed by institutions, leading to disagreements as to whom the final authority really is. Third and finally, the opinions of these authors are heavily cited on talk pages to allow editors to participate in the aforementioned authority of the author, ‘win’ talk page debates, and thereby establish a Wikipedia article that details the ‘One True Canon’.

The Gender Gap in Wikipedia Talk Pages

Wikipedia is an important source of information in today's world. Yet, the lack of gender diversity in its community has been shown to affect the topics covered. Each Wikipedia article has a talk page that volunteer editors use to discuss proposed changes. Research on the gender bias has focused on article contribution and topic coverage, but not talk page activity. It has been suggested that the conflicts that take place in talk pages are especially intimidating for women, but this assertion has not been quantified yet. To fill this gap, we collected a dataset of all comments on Wikipedia talk pages, enriching it with gender information available from users who have chosen to disclose their gender on their user profiles or settings. Among the users active in talk pages, 49,387 indicated that they are male while only 5,996 indicated that they are female. The comments of these users make up for 4 million comments, approximately one quarter of all comments on Wikipedia. In addition, we observed that female participation varies by topic, reflecting traditional gender stereotypes: compared to Science, Technology, Engineering and Mathematics (STEM) topics, women were more active in categories such as Gender studies or Feminism. Results also indicate that a post on a talk page is 2.4\% less likely to be replied to if the author is female. Likewise, reply probability varies from topic to topic. These results provide quantitative support for a gender bias in Wikipedia talk pages, and serve as a basis for discussing why overall female participation is low.

Evaluating a Computational Approach to Labeling Politeness

Social computing researchers are beginning to apply machine learning tools to classify and analyze social media data. Our interest in understanding politeness in an online community focused our attention on tools that would help automate politeness analysis. This paper highlights one popular classification tool designed to score the politeness of text. Our application of this tool to Wikipedia data yielded some unexpected results. Those unexpected results led us to question how the tool worked and its effectiveness relative to human judgment and classification. We designed a user study to revalidate the tool with crowdworkers labeling samples of content from Wikipedia talk pages, imitating the original efforts to validate the tool. This revalidation points to challenges for automatic labeling. Based on our results, this paper reconsiders politeness in online communities as well as broader trends in the use of machine classifiers in social computing research.

“A wound that has been festering since 2007”

PurposeThe Burma/Myanmar naming controversy on Wikipedia stands as an exemplary debate at least in terms of the politeness and civility of discourse. It was also one of the longer running debates on Wikipedia beginning almost at the same time as the creation of the article in 2003. But this debate has other lessons for those interested in one of the world’s key pieces of information infrastructure. The paper aims to discuss these issues.Design/methodology/approachThe author’s approach to the study of the Wikipedia talk pages devoted to the Burma/Myanmar naming controversy is qualitative in nature and explores the debate over sources through textual analysis.FindingsEditors brought to their work a number of underlying assumptions including the primacy of the nation-state and the nature of a “true” encyclopedia. These were combined with a particular interpretation of neutral point of view (NPOV) policy that unnecessarily prolonged the debate and, more importantly, would have the effect, if widely adopted, of reducing Wikipedia’s potential to include multiple perspectives on any particular topic.Originality/valueThe study clearly shows how editors tend to uncritically reproduce the dominant assumptions of their societies. When combined with positivist readings of NPOV policy, this has grave implications for Wikipedia’s potential to open up representation to a wider set of knowledge producers and perspectives. Much of this potential cannot be realized if the assumptions of editors, especially their flawed understanding of NPOV, cannot be challenged effectively.

Emotional Content in Wikipedia Articles on Negative Man-Made and Nature-Made Events

Wikipedia emphasizes the objectivity of content. Yet, Wikipedia articles also deal with negative events that potentially elicit intense emotions. Undesirable outcomes (e.g., earthquakes) are known to elicit sadness, while undesirable outcomes caused by others’ actions (e.g., terrorist attacks) are known to elicit anger. Internet users’ emotional responses are likely to end up in Wikipedia articles on those events as characteristics of Internet users spill over to Wikipedia articles. Therefore, we expected that Wikipedia articles on terrorist attacks contain more anger-related and less sadness-related content than articles on earthquakes. We analyzed newly created Wikipedia articles about the two events (Study 1) as well as more current versions of those Wikipedia articles after the events had already happened (Study 2). The results supported our expectations. Surprisingly, Wikipedia articles on those two events contained more emotional content than related Wikipedia talk pages (Study 3). We discuss the implications for Wikipedia and future research.

Digital discourse analysis and Wikipedia: Bridging the gap between Foucauldian discourse analysis and digital conversation analysis

In the last decade, analyzing online interaction rapidly gained in popularity and especially Wikipedia with its collaborative nature is a favored research object in linguistic studies. In discourse (linguistic) studies, there are some studies focusing on Wikipedia's encyclopedic article pages and others concentrating on conversational-like data on Wikipedia's talk pages. While the former can be located in the paradigm of Foucauldian discourse analysis, the latter have a rather conversation analytic approach. This paper gives an impulse to consider the convergence of data – namely the text-text convergence of article and talk pages on Wikipedia – by integrating digital conversation analysis (Giles et al., 2015) with Foucauldian discourse analysis (Spitzmüller and Warnke, 2011a). The paper begins to address this gap by conducting a detailed microanalysis on how discussions on talk pages impact on regimes of meaning on Wikipedia's article pages. The discourse fragment under investigation is the controversially discussed entry Annexation of Crimea by the Russian Federation. The considerations result in an analytic framework that integrates Foucauldian discourse analysis and digital conversation analysis. Therefore, this paper contributes to the discussion about digital conversation analysis by investigating digital discourses on Wikipedia. The microanalysis reveals communicative strategies and practices of interactivity on article pages and on corresponding talk pages. The peculiarities of Wikipedia's data will be explained, modes of analysis discussed and the challenges of the suggested integration of methods will be explored.

Wikipedia: a complex social machine by Ramine Tinati and Markus Luczak-Roesch with Martin Vesely as coordinator

Wikipedia represents a successful peer-produced knowledge-resource constructed via the endeav- ours of millions of volunteers. We examine the activity of Wikipedia by analysing WikiProjects, an community-driven feature which allows communities of Wikipedians to coordinate their efforts in order to improve or produce Wikipedia articles. We harvested the content of over 600 active Wikipedia projects, which comprised of over 100 million edits and 15 million Talk entries, associ- ated with over 1:5 million Wikipedia articles and Talk pages produced by 14 million unique users. Our analysis reveals findings related to the overall positive activity and growth of Wikipedia, as well as the connected community of Wikipedians within and between specific WikiProjects. We argue that the complexity of Wikipedia requires metrics which re ect the many aspects of the Wikipedia social machine, and by doing so, will offer insights into it's state of health.

Verifying social network models of Wikipedia knowledge community

The Wikipedia project has created one of the largest and best-known open knowledge communities. This community is a model for several similar efforts, both public and commercial, and even for the knowledge economy of the future e-society. For these reasons, issues of quality, social processes, and motivation within the Wikipedia knowledge community have attracted attention of researchers. Research has often used Social Network Analysis applied to networks created based on behavioral data available from the edit history of the Wikipedia.This paper asks the following question: are the popular assumptions about the social interpretations of networks created from the edit history valid? We verify commonly assumed interpretations of four types of networks created from discussions on Wikipedia talk pages, co-edits and reverts in Wikipedia articles, and edits of articles in various topics, by comparing these networks with results from a survey of editors of the Polish Wikipedia community. The results indicate that while the behavioral networks are strongly related to the declarations of respondents, only in one case of the network created from talk pages and interpreted as acquaintance we can observe a near equivalence. The article next describes improved definitions of behavioral indicators obtained through machine learning. The improved networks are much closer to their declarative counterparts.The main contribution of the article is a validated model of an acquaintance network among Wikipedia editors that can be derived from behavioral data and validly interpreted as acquaintance. Other contributions are improved versions of behavioral networks based on editing behavior and discussion history on the Wikipedia.

Debating reliable sources: writing the history of the Vietnam War on Wikipedia

Purpose – The purpose of this paper is to use selected discussions appearing on the talk pages of the Wikipedia entry on the Vietnam War to shed light on how the wider epistemological context of this online encyclopaedia affects the nature of debate about sources and subsequently how this knowledge could be used to improve information literacy instruction. Design/methodology/approach – My broad approach to the study of the Wikipedia talk pages on the Vietnam War is qualitative in nature and explores the debate over sources through a textual analysis. Findings – Although much of the debate over sources is conducted without acrimony, the level of analysis one finds in the talk pages is rather shallow while the attention of individual contributors is not overly concentrated. Originality/value – There have been few studies of individual Wikipedia entries and their talk pages, rather the focus of most of the literature has been on a broad overview of the entire encyclopaedia or a concentration on a set of entries for a particular topic area.

Building Linguistic Corpora from Wikipedia Articles and Discussions

Wikipedia is a valuable resource, useful as a lingustic corpus or a dataset for many kinds of research. We built corpora from Wikipedia articles and talk pages in the I5 format, a TEI customisation used in the German Reference Corpus (Deutsches Referenzkorpus DeReKo). Our approach is a two-stage conversion combining parsing using the Sweble parser, and transformation using XSLT stylesheets. The conversion approach is able to successfully generate rich and valid corpora regardless of languages. We also introduce a method to segment user contributions in talk pages into postings.

Inclusivity and Expert Knowledge: An Examination of Wikipedia Talk Pages and Reference Lists

Wikipedia relies on expertise to arbitrate rival knowledge claims (Sundin 2011). In choosing experts, Wikipedians define the boundaries of acceptable comment on any given subject. Inclusivity becomes a matter of how the boundaries of expertise are drawn. In this presentation I examine these boundaries and their implications as revealed through the talk pages produced and sources used by those Wikipedians writing articles on Philippine history.Wikipédia se base sur l’expertise pour arbitrer les assertions contradictoires (Sundin, 2011). En choisissant les experts, la communauté définit ce qui constitue un commentaire acceptable sur un sujet donné. L’inclusivité devient un concept sur lequel repose l’identification des frontières de l’expertise. Dans cette communication, j’examine ces frontières et leurs effets tels que révélés dans les pages de discussion produites et les sources utilisées par la communauté pour la rédaction d’articles sur l’histoire des Philippines.

Are We There Yet?: The Development of a Corpus Annotated for Social Acts in Multilingual Online Discourse

We present the AAWD and AACD corpora, a collection of discussions drawn from Wikipedia talk pages and small group IRC discussions in English, Russian and Mandarin. Our datasets are annotated with labels capturing two kinds of social acts: alignment moves and authority claims. We describe these social acts, describe our annotation process, highlight challenges we encountered and strategies we employed during annotation, and present some analyses of resulting data set which illustrate the utility of our corpus and identify interactions among social acts and between participant status and social acts and in online discourse.