Semantic Stability in Social Tagging Streams

One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet, previous research has provided interesting evidence that the tag distributions of resources may become semantically stable over time as more and more users tag them. At the same time, previous work has raised an array of new questions such as: (i) How can we assess the semantic stability of social tagging systems in a robust and methodical way? (ii) Does semantic stabilization of tags vary across different social tagging systems and ultimately, (iii) what are the factors that can explain semantic stabilization in such systems? In this work we tackle these questions by (i) presenting a novel and robust method which overcomes a number of limitations in existing methods, (ii) empirically investigating semantic stabilization processes in a wide range of social tagging systems with distinct domains and properties and (iii) detecting potential causes for semantic stabilization, specifically imitation behavior, shared background knowledge and intrinsic properties of natural language. Our results show that tagging streams which are generated by a combination of imitation dynamics and shared background knowledge exhibit faster and higher semantic stability than tagging streams which are generated via imitation dynamics or natural language streams alone

When Politicians Talk: Assessing Online Conversational Practices of Political Parties on Twitter

Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different - mostly qualitative - aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties.Comment: 10 pages, 2 figures, 3 tables, Proc. 8th International AAAI Conference on Weblogs and Social Media (ICWSM 2014

Online help-seeking in communities of practice

Interactive online help systems are considered to be a fruitful supplement to traditional IT helpdesks, which are often overloaded. They often comprise user-generated FAQ collections playing the role of technology-based conceptual artifacts. Two main questions arise: how the conceptual artifacts should be used, and which factors influence their acceptance in a community of practice (CoP). Firstly, this paper offers a theoretical frame and a usage scenario for technology-based conceptual artifacts against the theoretical background of the academic help-seeking and CoP approach. Each of the two approaches is extensively covered by psychological and educational research literature, however their combination is not yet sufficiently investigated. Secondly, the paper proposes a research model explaining the acceptance of conceptual artifacts. The model includes users’ expectations towards the artifact, perceived social influence and users’ roles in the CoP as predictors of artifact use intention and actual usage. A correlational study conducted in an academic software users’ CoP and involving structural equations modeling validates the model, suggesting thus a research line that is worth further pursuing. For educational practice, the study suggests three ways of supporting knowledge sharing in CoPs, i.e. use of technology-based conceptual artifacts, roles and division of labor, and purposeful communication in CoPs