Mining social media data from sparse text: an application to diplomacy

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dc.contributor.authorChua, Cecil
dc.contributor.authorLi, Xiaolin (David)
dc.contributor.authorKaul, Mala
dc.contributor.authorStorey, Veda C.
dc.contributor.editorParsons, Jeffrey
dc.contributor.editorTuunanen, Tuure
dc.contributor.editorVenable, John R.
dc.contributor.editorHelfert, Markus
dc.contributor.editorDonnellan, Brian
dc.contributor.editorKenneally, Jim
dc.contributor.funderNational University of Ireland, Maynoothen
dc.contributor.funderClaremont Graduate University, United Statesen
dc.contributor.funderMemorial University of Newfoundland, Canadaen
dc.date.accessioned2016-05-16T09:24:21Z
dc.date.available2016-05-16T09:24:21Z
dc.date.issued2016-05
dc.description.abstractPublicly available data in social media provides a wealth of unstructured data for applications, such as sentiment analysis and location-based services. This research analyzes a specific application of diplomats, who seek to understand the people with whom they must negotiate. Social media data about a negotiating partner can, potentially, be used to build a profile of that partner. However, such data is difficult to mine effectively because it has sparse text with high dimensionality. This research uses a design science approach to develop a method for extracting critical information from sparse text. The method mines sparse text from publically available Facebook data to extract patterns from individual communications. The method is applied to Facebook posts of a political figure to identify meaningful categories of information for insightful inferences. Preliminary evaluation shows support for the method.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationChua, C., Li, X. , Kaul, M., Storey, V. C. 2016. Mining social media data from sparse text: an application to diplomacy. In: Parsons, J., Tuunanen, T., Venable, J. R., Helfert, M., Donnellan, B., & Kenneally, J. (eds.) Breakthroughs and Emerging Insights from Ongoing Design Science Projects: Research-in-progress papers and poster presentations from the 11th International Conference on Design Science Research in Information Systems and Technology (DESRIST) 2016. St. John, Canada, 23-25 May. pp. 51-58en
dc.identifier.endpage58en
dc.identifier.isbn978-1-906642-85-3
dc.identifier.startpage51en
dc.identifier.urihttps://hdl.handle.net/10468/2566
dc.language.isoenen
dc.publisherDESRIST 2016en
dc.relation.ispartofBreakthroughs and Emerging Insights from Ongoing Design Science Projects: Research-in-progress papers and poster presentations from the 11th International Conference on Design Science Research in Information Systems and Technology (DESRIST) 2016. St. John, Canada, 23-25 May
dc.relation.urihttps://desrist2016.wordpress.com/
dc.rights©2016, The Author(s).en
dc.subjectDesign applicationen
dc.subjectDiplomaten
dc.subjectNatural language processingen
dc.subjectSentence clusteringen
dc.subjectSparse text miningen
dc.subjectSemantic chainen
dc.titleMining social media data from sparse text: an application to diplomacyen
dc.typeConference itemen
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