Negative emotions boost users activity at BBC Forum

We present an empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts. Nearly 2.5 million posts from over 18 thousand users were investigated. Scale free distributions were observed for activity in individual discussion threads as well as for overall activity. The number of unique users in a thread normalized by the thread length decays with thread length, suggesting that thread life is sustained by mutual discussions rather than by independent comments. Automatic sentiment analysis shows that most posts contain negative emotions and the most active users in individual threads express predominantly negative sentiments. It follows that the average emotion of longer threads is more negative and that threads can be sustained by negative comments. An agent based computer simulation model has been used to reproduce several essential characteristics of the analyzed system. The model stresses the role of discussions between users, especially emotionally laden quarrels between supporters of opposite opinions, and represents many observed statistics of the forum.Comment: 29 pages, 6 figure

Collective emotions online and their influence on community life

E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information - how participants feel about the subject discussed or other group members. Emotions are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. It is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. We show the collective character of affective phenomena on a large scale as observed in 4 million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.Comment: 23 pages including Supporting Information, accepted to PLoS ON

Field Report: "Why Democracy?"

Evaluates the public broadcasting collaboration "Why Democracy?" and its efforts to coordinate international broadcast events and to use the digital social networking space to host discussions of public issues. Outlines challenges and lessons learned

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

‘Friends call me racist’: Experiences of repercussions from writing comments on newspaper websites

acceptedVersio

Jesus and Metal Music Don’t Mix? : The Controversy over the “Metal Mass” in Finland

In 2006, a Metal Mass—a regular Lutheran mass with accompanying metal music—was celebrated in Helsinki and created a controversy on several online forums. On the one hand, the focus was the appropriateness of metal music in the context of a Christian mass. On the other hand, the issue at stake was the appropriateness of Christianity in the context of metal music and culture. In this article, we concentrate on how the controversy over the boundaries of 'good' religion is constructed in discourse about the appropriateness of metal music in the context of a national church and its services. We argue that the controversy over the Metal Mass is a case of broader negotiation between the function and performance of religious actors in contemporary Finland, yet when it happens within a secularized context, the temporarily full pews turn out to be an anomaly rather than a sign of revival.Peer reviewe

Web based lecture technologies: blurring the boundaries between face to face and distance learning

Web based lecture technologies (WBLT) have gained popularity amongst universities in Australia as a tool for delivering lecture recordings to students in close to real time. This paper reports on a selection of results from a larger research project investigating the impact of WBLT on teaching and learning. Results show that while staff see the advantages for external students, they question the extent to which these advantages apply to internal students. In contrast both cohorts of students were positive about the benefits of the technologies for their learning and they adopted similar strategies for their use. With the help of other technologies, some external students and staff even found WBLT useful for fostering communication between internal and external students. As such, while the traditional boundary between internal and external students seems to remain for some staff, students seem to find the boundary much less clear

Building and Executing MOOCs: A Practical Review of Glasgow's First Two MOOCs (Massive Open Online Courses)

No abstract available

Crowdsourcing as a way to access external knowledge for innovation

This paper focuses on “crowdsourcing” as a significant trend in the new paradigm of open innovation (Chesbrough 2006; Chesbrough & Appleyard 2007). Crowdsourcing conveys the idea of opening the R&D processes to “the crowd” through a web 2.0 infrastructure. Based on two cases studies of crowdsourcing webstartups (Wilogo and CrowdSpirit), the paper aims to build a framework to characterize and interpret the tension between value creation by a community and value capture by a private economic actor. Contributing to the discussions on “hybrid organizational forms” in organizational studies (Bruce & Jordan 2007), the analysis examines how theses new models combine various forms of relationships and exchanges (market or non market). It describes how crowdsourcing conveys new patterns of control, incentives and co-ordination mechanisms.communauté ; crowdsourcing ; innovation ; formes organisationnelles hybrides ; plateforme ; web 2.0