Linked data in crowdsourcing purposive social network

Singh, Priyanka; Shadbolt, Nigel

doi:10.1145/2487788.2488079

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…The first measurement we use for content quality is the number of votes on question/answer, which is one of the most direct and commonly used measurements of content quality in Q&A communities 3 [35]. Particularly we calculated the net votes by counting the up-votes minus down-votes.…”

Section: Measuring Qualitymentioning

confidence: 99%

Is It Good to Be Like Wikipedia?

Zhu

et al. 2015

Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work &Amp; Social Computing

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Online question and answer (Q&A) sites, which are platforms for users to post and answer questions on a wide range of topics, are becoming large repositories of valuable knowledge and important to societies. In order to sustain success, Q&A sites face the challenges of ensuring content quality and encouraging user contributions. This paper examines a particular design decision in Q&A sitesallowing Wikipedia-like collaborative editing on questions and answers, and explores its beneficial effects on content quality and potential detrimental effects on users' contributions. By examining five years' archival data of Stack Overflow, we found that the benefits of collaborative editing outweigh its risks. For example, each substantive edit from other users can increase the number of positive votes by 181% for the questions and 119% for the answers. On the other hand, each edit only decreases askers and answerers' subsequent contributions by no more than 5%. This work has implications for understanding and designing large-scale social computing systems.

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Section: Measuring Qualitymentioning

confidence: 99%

Is It Good to Be Like Wikipedia?

Zhu

et al. 2015

Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work &Amp; Social Computing

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“…(Crowley, Breslin, Corcoran, & Young, 2012;Crowston & Prestopnik, 2013)) or social networking sites (e.g. (Hsu, Chang, & Lee, 2013;Singh & Shadbolt, 2013)). Others are using the mental power of communities in order to complete some repetitive tasks that "…computers are unable to perform."…”

Section: Realization Of Gamificationmentioning

confidence: 99%

Project Knowledge Management While Simply Playing! Gaming Mechanics in Project Knowledge Management Systems

Schacht

Maedche

2014

Gamification in Education and Business

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In addition to challenges caused by the project itself, a project manager is exposed to many questions and obstacles regarding project knowledge management (KM). Beginning with project's start, the first task of project managers is to decide which expert fits best to the team. Thus, he has to figure out who knows what. Within the project, a vast amount of knowledge is created and shared among all project participants. The individual knowledge base of each member is growing rapidly in the limited period of time until the project is finished. Furthermore, members are joining or leaving the team which also increases the heterogeneity of overall project knowledge. Finally, at project's end, the project manager is ordered by his supervisor to collect and document project's key insights. These insights are called lessons learned and aim to improve organizational learning. Often, the collection and documentation of lessons learned take place in a final team meeting. This final step again comes along with a number of questions: Who has to be invited? Since team members join and leave the project during its duration, it is difficult to sample the group of appropriate participants. Have invitees time to join the session? Often, project team members already left the project or immediately joined another team or project. Therefore, invitees rate the benefits of participating at lessons learned sessions as being very low. Are the invitees motivated to participate and

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“…Stack-Overflow have more than 3.2 million questions and 1.2 million registered users. Despite so many users, 23.7% of questions in StackOverflow do not get any answers [33]. There is a long tail of questions that get no answer or votes.…”

Section: Introductionmentioning

confidence: 99%

Using Semantics to Search Answers for Unanswered Questions in Q&A Forums

Singh

Simperl

2016

Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion

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The expert based question and answering forums are crowdsourced and rely on people to provide answers for questions. This paper focuses on technology based Q&A systems like StackOverflow and Reddit. These websites are popular and yet many questions remain unanswered. The Suman system uses semantic keyword search in combination with traditional text search techniques to find similar questions with answers for unanswered questions. Furthermore, the Suman system also recommends experts who can answer those questions. This helps to narrow down the long tail of unanswered questions. The Suman system utilises Semantic Web and Linked Data technologies to integrate the datasets from two websites, structure them and link them to Linked Data Cloud. It uses available tools to solve name entity disambiguation problem and expands the query term with added semantics. The Suman system was evaluated and results were analysed to show its viability.

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Linked data in crowdsourcing purposive social network

Cited by 7 publications

References 14 publications

Is It Good to Be Like Wikipedia?

Is It Good to Be Like Wikipedia?

Project Knowledge Management While Simply Playing! Gaming Mechanics in Project Knowledge Management Systems

Using Semantics to Search Answers for Unanswered Questions in Q&A Forums

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