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"Online social networks Encyclopedias."
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Developing an online hate classifier for multiple social media platforms
The proliferation of social media enables people to express their opinions widely online. However, at the same time, this has resulted in the emergence of conflict and hate, making online environments uninviting for users. Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. To address this research gap, we collect a total of 197,566 comments from four platforms: YouTube, Reddit, Wikipedia, and Twitter, with 80% of the comments labeled as non-hateful and the remaining 20% labeled as hateful. We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). While all the models significantly outperform the keyword-based baseline classifier, XGBoost using all features performs the best (F1 = 0.92). Feature importance analysis indicates that BERT features are the most impactful for the predictions. Findings support the generalizability of the best model, as the platform-specific results from Twitter and Wikipedia are comparable to their respective source papers. We make our code publicly available for application in real software systems as well as for further development by online hate researchers.
Journal Article
Emergent Life Cycle: The Tension Between Knowledge Change and Knowledge Retention in Open Online Coproduction Communities
Online coproduction communities often face a challenge of whether to change or retain the knowledge they have created. Disparate and often conflicting theoretical models have been used to explain how these communities respond to this tension. We conducted a case study of how one online coproduction community—the nine-year history of the Wikipedia article on autism—handles this tension. We find that the nature of the change–retain tension and the community’s response to it fluctuates considerably over the life of the community. These changes bear striking similarities to processes associated with traditional software development life cycles, despite the absence of traditional control mechanisms. What initially appear to be conflicts in the extant literature actually describe different roles and production focus at the different stages of development. Disruptive events signal the need for the community to shift production focus, which often involves members joining and leaving the production process, rather than adopting new roles.
This paper was accepted by Sandra Slaughter, information systems.
Journal Article
The Impact of Membership Overlap on Growth: An Ecological Competition View of Online Groups
The dominant narrative of the Internet has been one of unconstrained growth, abundance, and plenitude. It is in this context that new forms of organizing, such as online groups, have emerged. However, the same factors that underlie the utopian narrative of Internet life also give rise to numerous online groups, many of which fail to attract participants or to provide significant value. This suggests that despite the potential transformative nature of modern information technology, issues of scarcity, competition, and context may remain critical to the performance and functioning of online groups. In this paper, we draw from organizational ecology theories to develop an ecological view of online groups to explain how overlapping membership among online groups causes intergroup competition for member attention and affects a group's ability to grow. Hypotheses regarding the effects of group size, age, and membership overlap on growth are proposed and tested with data from a 64-month, longitudinal sample of 240 online discussion groups. The analysis shows that sharing members with other groups reduced future growth rates, suggesting that membership overlap puts competitive pressure on online groups. Our results also suggest that, compared with smaller and younger groups, larger and older groups experience greater difficulty in growing their membership. In addition, larger groups were more vulnerable to competitive pressure than smaller groups: larger groups experienced greater difficulty in growing their membership than smaller groups as competition intensified. Overall, our findings show how an abundance of opportunities afforded by technologies can create scarcity in user time and effort, which increases competitive pressure on online groups. Our ecological view extends organizational ecology theory to new organizational forms online and highlights the importance of studying the competitive environment of online groups.
Journal Article
A relationship extraction method for domain knowledge graph construction
As a semantic knowledge base, knowledge graph is a powerful tool for managing large-scale knowledge consists with instances, concepts and relationships between them. In view that the existing domain knowledge graphs can not obtain relationships in various structures through targeted approaches in the process of construction which resulting in insufficient knowledge utilization, this paper proposes a relationship extraction method for domain knowledge graph construction. We obtain upper and lower relationships from structured data in the classification system of network encyclopedia and semi-structured data in the classification labels of web pages, and non-superordinate relationships are extracted from unstructured text through the proposed convolution residual network based on improved cross-entropy loss function. We verify the effectiveness of the designed method by comparing with existing relationship extraction methods and constructing a food domain knowledge graph.
Journal Article
How offline meetings affect online activities: the case of Wikipedia
As open-source communities and other peer production projects face the challenge of sustaining themselves over time, the role of offline gatherings in fostering community resilience becomes a vital question. This study centres on the potential of offline social interactions as a means to mitigate declines within such communities, using Wikipedia as a case example. Using a comprehensive dataset spanning informal meetups within the German-language Wikipedia community from 2001 to 2020 and combining it with large scale online activity data, this study investigates the relationship between offline gatherings and online contribution behaviour. Results show that attending meetups has a positive effect on contributing towards Wikipedia both in the short and long term. By shedding light on the significance of offline social interactions in bolstering online communities, this study offers valuable insights into potential strategies for sustaining collaborative online environments amidst broader declines and further shows how offline and online activities intertwine.
Journal Article
Does Passive Facebook Use Promote Feelings of Social Connectedness?
Previous research has shown that passive social media use does not have the same positive effects on well-being as active social media use. However, it is currently unclear whether these effects can be attributed to the benefits of active use, the costs of passive use, or both. The current article investigated the effect of active and passive Facebook use on feelings of social connectedness after being ostracized. In two preregistered experiments, participants were first ostracized on a faux social media platform, followed by a measurement of social connectedness. In Experiment 1 they were then instructed to either use Facebook passively, use Facebook actively, or use a non-social website (Wikipedia), after which social connectedness was measured again. Results indicated that active Facebook use can restore social connectedness after being ostracized as compared to using a non-social website. While passive Facebook use also restored social connectedness, it did not change social connectedness significantly more so than Wikipedia use. In Experiment 2, we replicated Experiment 1, now focusing only on passive Facebook use compared to a non-social website. Results showed again that passive Facebook use did not influence social connectedness more so than the use of Wikipedia. In exploratory analyses, we found that for participants who felt close to other Facebook users, passive Facebook use did increase social connectedness compared to using a non-social website. These experiments suggest that, even though passive social media use does not restore social connectedness in the same way that active social media use does, it also does not harm social connectedness, and it may actually promote social connectedness under certain circumstances.
Journal Article
Milgram’s experiment in the knowledge space: individual navigation strategies
Data deluge characteristic for our times has led to information overload, posing a significant challenge to effectively finding our way through the digital landscape. Addressing this issue requires an in-depth understanding of how we navigate through the abundance of information. Previous research has discovered multiple patterns in how individuals navigate in the geographic, social, and information spaces, yet individual differences in strategies for navigation in the knowledge space has remained largely unexplored. To bridge the gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed questionnaires about their personal information. Utilizing the hierarchical structure of the English Wikipedia and a graph embedding trained on it, we identified two navigation strategies and found that there are significant individual differences in the choices of them. Older, white and female participants tend to adopt a proximity-driven strategy, while younger participants prefer a hub-driven strategy. Our study connects social navigation to knowledge navigation: individuals’ differing tendencies to use geographical and occupational information about the target person to navigate in the social space can be understood as different choices between the hub-driven and proximity-driven strategies in the knowledge space.
Journal Article
Toxic comments are associated with reduced activity of volunteer editors on Wikipedia
Abstract
Wikipedia is one of the most successful collaborative projects in history. It is the largest encyclopedia ever created, with millions of users worldwide relying on it as the first source of information as well as for fact-checking and in-depth research. As Wikipedia relies solely on the efforts of its volunteer editors, its success might be particularly affected by toxic speech. In this paper, we analyze all 57 million comments made on user talk pages of 8.5 million editors across the six most active language editions of Wikipedia to study the potential impact of toxicity on editors’ behavior. We find that toxic comments are consistently associated with reduced activity of editors, equivalent to 0.5–2 active days per user in the short term. This translates to multiple human-years of lost productivity, considering the number of active contributors to Wikipedia. The effects of toxic comments are potentially even greater in the long term, as they are associated with a significantly increased risk of editors leaving the project altogether. Using an agent-based model, we demonstrate that toxicity attacks on Wikipedia have the potential to impede the progress of the entire project. Our results underscore the importance of mitigating toxic speech on collaborative platforms such as Wikipedia to ensure their continued success.
Journal Article
The colonization of Wikipedia: evidence from characteristic editing behaviors of warring camps
PurposeTo add new empirical knowledge to debates about social practices of peer production communities, and to conversations about bias and its implications for democracy. To help identify Wikipedia (WP) articles that are affected by systematic bias and hopefully help alleviate the impact of such bias on the general public, thus helping enhance both traditional (e.g. libraries) and online information services (e.g. Google) in ways that contribute to democracy. This paper aims to discuss the aforementioned objectives.Design/methodology/approachQuantitatively, the authors identify edit-warring camps across many conflict zones of the English language WP, and profile and compare success rates and typologies of camp edits in the corresponding topic areas. Qualitatively, the authors analyze the edit war between two senior WP editors that resulted in imbalanced and biased articles throughout a topic area for such editorial characteristics through a close critical reading.FindingsThrough a large-scale quantitative study, the authors find that winner-take-all camps exhibit biasing editing behaviors to a much larger extent than the camps they successfully edit-war against, confirming findings of prior small-scale qualitative studies. The authors also confirm the employment of these behaviors and identify other behaviors in the successful silencing of traditional medicinal knowledge on WP by a scientism-biased senior WP editor through close reading.Social implicationsWP sadly does, as previously claimed, appear to be a platform that represents the biased viewpoints of its most stridently opinionated Western white male editors, and routinely misrepresents scholarly work and scientific consensus, the authors find. WP is therefore in dire need of scholarly oversight and decolonization.Originality/valueThe authors independently verify findings from prior personal accounts of highly power-imbalanced fights of scholars against senior editors on WP through a third-party close reading of a much more power balanced edit war between senior WP editors. The authors confirm that these findings generalize well to edit wars across WP, through a large scale quantitative analysis of unbalanced edit wars across a wide range of zones of contention on WP.
Journal Article