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Classifying business types from twitter posts using active learning

dc.contributor.authorThongsuk, Chanattha
dc.contributor.authorHaruechaiyasak, Choochart
dc.contributor.authorMeesad, Phayung
dc.contributor.editorEichler, Gerald
dc.contributor.editorKropf, Peter
dc.contributor.editorLechner, Ulrike
dc.contributor.editorMeesad, Phayung
dc.contributor.editorUnger, Herwig
dc.date.accessioned2019-01-11T09:33:30Z
dc.date.available2019-01-11T09:33:30Z
dc.date.issued2010
dc.description.abstractToday, many companies have adopted Twitter as an additional marketing medium to advertise and promote their business activities. One possible solution for organizing a large number of posts is to classify them into a predefined category of business types. Applying normal text categorization technique on Twitter is ineffective due to the short-length (140-character limit) characteristic of each post and a large number of unlabeled data. In this paper, we propose a text categorization approach based on the active learning technique for classifying Twitter posts into three business types, i.e., airline, food and computer & technology. By applying the active learning, we started by constructing an initial text categorization model from a small set of labelled data. Using this text categorization model, we obtain more positive data instances for constructing a new model by selecting the test data which are predicted as positive. As shown from the experimental results, our proposed approach based on active learning helped increase the classification accuracy over the normal text categorization approach.en
dc.identifier.isbn978-3-88579-259-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/19013
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof10th International Conferenceon Innovative Internet Community Systems (I2CS) – Jubilee Edition 2010 –
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-165
dc.titleClassifying business types from twitter posts using active learningen
dc.typeText/Conference Paper
gi.citation.endPage189
gi.citation.publisherPlaceBonn
gi.citation.startPage180
gi.conference.dateJune 3-5, 2010
gi.conference.locationBangkok, Thailand
gi.conference.sessiontitleRegular Research Papers

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