2020
DOI: 10.1007/s10796-020-10059-8
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Sustaining Open Source Communities by Understanding the Influence of Discursive Manifestations on Sentiment

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Cited by 6 publications
(3 citation statements)
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“…In doing so, we ultimately help IS theory to take steps away from the traditional "what" questions and move towards the more insightful "how" ones, while we contribute to the line of IS research on theorising using large datasets and novel computational approaches (Kar & Dwivedi, 2020). Concurrently, we contribute to the ongoing discussions on community emergence and evolution within the broader IS literature, especially on those around communities of consumption (e.g., Wang et al, 2019), brand communities (e.g., Fetais, et al, 2022Kannan et al, 2000;Santos et al, 2022), experiential communities (e.g., Canevez et al, 2022;Dennehy et al, 2020;Kamboj et al, 2018;Prakasam & Huxtable-Thomas, 2021) and consumer tribes (e.g., Gloor et al, 2020;Xu et al, 2019), as well as those around interpersonal (e.g., Dong et al, 2021) or resource dynamics (e.g., Wang et al, 2021) on communities. Finally, as the IS field is increasingly adopting such computational approaches (e.g., Georgiadou et al, 2020), and is opening up to new perspectives (e.g., Kar & Dwivedi, 2020), the approach we have incorporated in can further enhance the endeavours on theorizing through the use of large datasets, and, as we have demonstrated, become powerful tools for meta-analysis applications.…”
Section: Theoretical Implicationsmentioning
confidence: 91%
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“…In doing so, we ultimately help IS theory to take steps away from the traditional "what" questions and move towards the more insightful "how" ones, while we contribute to the line of IS research on theorising using large datasets and novel computational approaches (Kar & Dwivedi, 2020). Concurrently, we contribute to the ongoing discussions on community emergence and evolution within the broader IS literature, especially on those around communities of consumption (e.g., Wang et al, 2019), brand communities (e.g., Fetais, et al, 2022Kannan et al, 2000;Santos et al, 2022), experiential communities (e.g., Canevez et al, 2022;Dennehy et al, 2020;Kamboj et al, 2018;Prakasam & Huxtable-Thomas, 2021) and consumer tribes (e.g., Gloor et al, 2020;Xu et al, 2019), as well as those around interpersonal (e.g., Dong et al, 2021) or resource dynamics (e.g., Wang et al, 2021) on communities. Finally, as the IS field is increasingly adopting such computational approaches (e.g., Georgiadou et al, 2020), and is opening up to new perspectives (e.g., Kar & Dwivedi, 2020), the approach we have incorporated in can further enhance the endeavours on theorizing through the use of large datasets, and, as we have demonstrated, become powerful tools for meta-analysis applications.…”
Section: Theoretical Implicationsmentioning
confidence: 91%
“…The extant information systems (IS) literature has investigated various types of communities, such as communities of consumption (e.g., Algharabat & Rana, 2021;Mirkovski et al, 2019;Wang et al, 2019), brand communities (e.g., Fetais et al, 2022;Kannan et al, 2000;Santos et al, 2022), experiential communities (e.g., Canevez et al, 2022;Dennehy et al, 2020;Kamboj et al, 2018;Prakasam & Huxtable-Thomas, 2021) and consumer tribes (e.g., Gloor et al, 2020;Xu et al, 2019). This line of research has documented that: i) social interactions strengthen the bonds amongst community members, ii) identity-relevant symbolic meanings encourage community membership, and iii) practices, such as welcoming, badging, and signalling prolong the vitality of a community.…”
Section: Introductionmentioning
confidence: 99%
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