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Using linked data in purposive social networks

Using linked data in purposive social networks
Using linked data in purposive social networks
The Web has provided a platform for people to collaborate by using collective intelligence. Messaging boards, Q&A forums are some examples where people broadcast their issues and other people provide solutions. Such communities are defined as a Purposive Social Network (PSN) in this thesis. PSN is a community where people with similar interest and varied expertise come together, use collective intelligence to solve common problems in the community and build tools for common purpose. Usually, Q&A forums are closed or semi-open. The data are controlled by the websites. Difficulties in the search and discovery of information is an issue. People searching for answers or experts in a website can only see results from its own network, while losing a whole community of experts in other websites. Another issue in Q&A forums is not getting any response from the community. There is a long tail of questions that get no answer.The thesis introduces the Suman system that utilises Semantic Web (SW) and Linked Data technologies to solve above challenges. SW technologies are used to structure the community data so it can be decentralized and used across platforms. Linked Data helps to find related information about linked resources. The Suman system uses available tools to solve name entity disambiguation problem and add semantics to the PSN data. It uses a novel combination of semantic keyword search with traditional text search techniques to find similar questions with answers for unanswered questions to expand the query term with added semantics and uses crowd sourced data to rank the results. Furthermore, the Suman system also recommends experts who can answer those questions. This helps to narrow down the long tail of unanswered questions in such communities.The Suman system is designed using the Design Science methodology and evaluated by users in two experiments. The results were statistically analysed to show that the keywords generated by the Suman system were rated higher than the original keywords from the websites. It also showed that the participants agreed with the algorithm rating for answers provided by the Suman system. StackOverflow and Reddit are used as an example of PSN and to build an application as a proof of concept of the Suman system.
University of Southampton
Singh, Priyanka
9114f1a3-01e1-47d1-a62c-76ea537c764e
Singh, Priyanka
9114f1a3-01e1-47d1-a62c-76ea537c764e
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67

Singh, Priyanka (2016) Using linked data in purposive social networks. University of Southampton, Doctoral Thesis, 250pp.

Record type: Thesis (Doctoral)

Abstract

The Web has provided a platform for people to collaborate by using collective intelligence. Messaging boards, Q&A forums are some examples where people broadcast their issues and other people provide solutions. Such communities are defined as a Purposive Social Network (PSN) in this thesis. PSN is a community where people with similar interest and varied expertise come together, use collective intelligence to solve common problems in the community and build tools for common purpose. Usually, Q&A forums are closed or semi-open. The data are controlled by the websites. Difficulties in the search and discovery of information is an issue. People searching for answers or experts in a website can only see results from its own network, while losing a whole community of experts in other websites. Another issue in Q&A forums is not getting any response from the community. There is a long tail of questions that get no answer.The thesis introduces the Suman system that utilises Semantic Web (SW) and Linked Data technologies to solve above challenges. SW technologies are used to structure the community data so it can be decentralized and used across platforms. Linked Data helps to find related information about linked resources. The Suman system uses available tools to solve name entity disambiguation problem and add semantics to the PSN data. It uses a novel combination of semantic keyword search with traditional text search techniques to find similar questions with answers for unanswered questions to expand the query term with added semantics and uses crowd sourced data to rank the results. Furthermore, the Suman system also recommends experts who can answer those questions. This helps to narrow down the long tail of unanswered questions in such communities.The Suman system is designed using the Design Science methodology and evaluated by users in two experiments. The results were statistically analysed to show that the keywords generated by the Suman system were rated higher than the original keywords from the websites. It also showed that the participants agreed with the algorithm rating for answers provided by the Suman system. StackOverflow and Reddit are used as an example of PSN and to build an application as a proof of concept of the Suman system.

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Published date: September 2016
Organisations: University of Southampton

Identifiers

Local EPrints ID: 409708
URI: http://eprints.soton.ac.uk/id/eprint/409708
PURE UUID: 7e8bee14-2ce8-4b71-90b5-de1c74fc00a5
ORCID for Elena Simperl: ORCID iD orcid.org/0000-0003-1722-947X

Catalogue record

Date deposited: 01 Jun 2017 04:06
Last modified: 20 Jul 2019 00:40

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Contributors

Author: Priyanka Singh
Thesis advisor: Elena Simperl ORCID iD

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