Evolution of Experts in Question Answering Communities

Pal, Aditya; Chang, Shuo; Konstan, Joseph A.

doi:10.1609/icwsm.v6i1.14262

Cited by 34 publications

(7 citation statements)

References 20 publications

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“…Researchers have studied Stack Exchange sites, and especially Stack Overflow, for various purposes. Among those, data from the discussions were used to discover the evolution of topic trends in a developer community [ 43 , 44 ], to predict answer quality [ 45 ] or user participation [ 46 ], to identify experts [ 47 ], to recommend solutions to programming errors [ 48 ], and to analyze social interactions inside the cooperative community [ 49 , 50 ]. The collaborative tagging system applied within the communities and its implications have also been the focus of previous work [ 17 , 26 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

Associative linking for collaborative thinking: Self-organization of content in online Q&A communities via user-generated links

Sher,

Rafaeli

2024

PLoS ONE

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Virtual collaborative Q&A communities generate shared knowledge through the interaction of people and content. This knowledge is often fragmented, and its value as a collective, collaboratively formed product, is largely overlooked. Inspired by work on individual mental semantic networks, the current study explores the networks formed by user-added associative links as reflecting an aspect of self-organization within the communities’ collaborative knowledge sharing. Using eight Q&A topic-centered discussions from the Stack Exchange platform, it investigated how associative links form internal structures within the networks. Network analysis tools were used to derive topological indicator metrics of complex structures from associatively-linked networks. Similar metrics extracted from 1000 simulated randomly linked networks of comparable sizes and growth patterns were used to generate estimated sampling distributions through bootstrap resampling, and 99% confidence intervals were constructed for each metric. The discussion-network indicators were compared against these. Results showed that participant-added associative links largely led to networks that were more clustered, integrated, and included posts with more connections than those that would be expected in random networks of similar size and growth pattern. The differences were observed to increase over time. Also, the largest connected subgraphs within the discussion networks were found to be modular. Limited qualitative observations have also pointed to the impacts of external content-related events on the network structures. The findings strengthen the notion that the networks emerging from associative link sharing resemble other information networks that are characterized by internal structures suggesting self-organization, laying the ground for further exploration of collaborative linking as a form of collective knowledge organization. It underscores the importance of recognizing and leveraging this latent mechanism in both theory and practice.

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Section: Methodsmentioning

confidence: 99%

Associative linking for collaborative thinking: Self-organization of content in online Q&A communities via user-generated links

Sher,

Rafaeli

2024

PLoS ONE

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“…Therefore, we introduced additional measure to consider individual expertise as a PLOS ONE control variable. Prior research has emphasized that users' expertise tends to evolve on CQA platforms [83,84]. Acknowledging the limitations of observational data in directly measuring expertise or domain knowledge, we utilize badges earned by individuals prior to answer contribution as a proxy.…”

Section: Robustness Checksmentioning

confidence: 99%

“The double-edged sword of inflated help”: Unravelling the motivation crowding in community question-answering platforms

Krishna,

Shrestha,

von Krogh

2024

PLoS ONE

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The growth of digital platforms has led to the proliferation of Online Communities, providing individuals with opportunities to seek help and share knowledge. A key challenge of help-related platforms that address technical questions (i.e., utilitarian, rather than opinion or supportive) is to ensure the contributions address seekers’ specific information needs. Despite growing academic interest in such platforms, research has mainly focused on factors that influence the quantity of contributions, ignoring whether these contributions effectively helped the seekers. To fill this research gap, this study draws upon theories of self-determination and motivation crowding to examine contributing behaviors that result in successful helping. By analyzing a rich dataset collected from an online Q&A platform, we find that gains in a help provider’s past rewards positively influence the success of contribution. Further, while previous studies suggest that external rewards result in a high quantity of contribution, our findings show that an inflated frequency of contribution leads to a crowding-out effect. Specifically, the contribution frequency has a curvilinear relationship with the success of the contribution. Taken together, these findings demonstrate there is a need to revisit the gamification mechanism on help-related platforms to ensure the success of knowledge contribution. This is crucial for the sustainability of these platforms as low-quality answers can lead users to mistrust and eventually leave the platform.

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“…Such communities have been extensively utilized to conduct studies in the field of software engineering. For example, Stack Overflow, which is the largest and most visited Q&A website, has been used as a source to efficiently identify architecturally relevant knowledge [21], investigate the relationships between architecture patterns and quality attributes [22], examine users' behaviors and topic trends [23], [24], study architecture smells [13], and explore anti-patterns and code smells [12]. In addition, other popular online developer communities are also used for research in software engineering, for example, understanding social and technical factors of contributions in GitHub [25].…”

Section: B Online Developer Communitiesmentioning

confidence: 99%

Understanding Architecture Erosion: The Practitioners’ Perceptive

Liang

Soliman

et al. 2021

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)

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As software systems evolve, their architecture is meant to adapt accordingly by following the changes in requirements, the environment, and the implementation. However, in practice, the evolving system often deviates from the architecture, causing severe consequences to system maintenance and evolution. This phenomenon of architecture erosion has been studied extensively in research, but not yet been examined from the point of view of developers. In this exploratory study, we look into how developers perceive the notion of architecture erosion, its causes and consequences, as well as tools and practices to identify and control architecture erosion. To this end, we searched through several popular online developer communities for collecting data of discussions related to architecture erosion. Besides, we identified developers involved in these discussions and conducted a survey with 10 participants and held interviews with 4 participants. Our findings show that: (1) developers either focus on the structural manifestation of architecture erosion or on its effect on run-time qualities, maintenance and evolution;(2) alongside technical factors, architecture erosion is caused to a large extent by non-technical factors; (3) despite the lack of dedicated tools for detecting architecture erosion, developers usually identify erosion through a number of symptoms; and (4) there are effective measures that can help to alleviate the impact of architecture erosion.

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Evolution of Experts in Question Answering Communities

Cited by 34 publications

References 20 publications

Associative linking for collaborative thinking: Self-organization of content in online Q&A communities via user-generated links

Associative linking for collaborative thinking: Self-organization of content in online Q&A communities via user-generated links

“The double-edged sword of inflated help”: Unravelling the motivation crowding in community question-answering platforms

Understanding Architecture Erosion: The Practitioners’ Perceptive

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