Characterizing Silent Users in Social Media Communities
By Wei Gong, Ee-Peng Lim, Feida Zhu. 2015
88 citations recorded by the source corpus.
Silent users often constitute a significant proportion of an online user-generated content system. In the context of social media such as Twitter, users can opt to be silent all or most of the time. They are often called the invisible participants or lurkers. As lurkers contribute little to the online content, existing analysis often overlooks their presence and voices. However, we argue that understanding lurkers is important in many applications such as recommender systems, targeted advertising, and social sensing. This research therefore seeks to characterize lurkers in social media and propose methods to profile them. We examine 18 weeks of tweets generated by two Twitter communities consisting of more than 110K and 114K users respectively. We find that there are many lurkers in the two communities, and the proportion of lurkers in each community changes with time.We also show that by leveraging lurkers' neighbor content, we are able to profile them with accuracy comparable to that of profiling active users. It suggests that user generated content can be utilized for profiling lurkers and lurkers in Twitter are after all not that ``invisible''.
Subfields: Information Systems, Sociology and Political Science, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Fernando Diaz
- Alexandra Olteanu
- Carlos Castillo
- Emre Kıcıman
- Ee-Peng Lim
- Onur Varol
- David Jurgens
- Derek Ruths
In Sociology and Political Science
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Feida Zhu
- Ee-Peng Lim
- Wei Gong
- Onur Varol
In Statistical and Nonlinear Physics
- Alexandra Olteanu
- Carlos Castillo
- Fernando Diaz
- Emre Kıcıman
- Feida Zhu
- Ee-Peng Lim
- Wei Gong
- Onur Varol
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “In the case of inactive accounts, Gong et al. (2015, 2016) found that a significant fraction of users, though interested in a given topic, choose to remain silent.”
- On Unravelling Opinions of Issue Specific-Silent Users in Social Media (2016, background): “Hence, they may not be overall silent users who do not post anything or post only a little in a long period time (Tagarelli and Interdonato 2013; Gong, Lim, and Zhu 2015).”
- Distilling the Outcomes of Personal Experiences: A Propensity-scored Analysis of Social Media (2017, background): “these experiences, as users may often chose to remain “silent” on various topics [46].”
- User Migration in Online Social Networks: A Case Study on Reddit During a Period of Community Unrest (2016, background): “Many users do not comment and fewer still create posts; these users represent a large silent majority, a phenomenon which is observed on many other types of social media (Benevenuto et al. 2009; Bernstein et al. 2013; Gong, Lim, and Zhu 2015).”