{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T15:52:24Z","timestamp":1687535544357},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,2,28]]},"abstract":"Abstract<\/jats:title>\n Social networking services have become a major channel for the digital\nsociety to share content, opinions, experiences on activities or\nevents, as well as on products, services and brands. Evaluating\ndigital feedback on the latter can be a valuable asset for companies\nseeking product and consumer insights. However, the analysis of\nshort, noisy, fragmented, and often subjective textual data still\nremains a challenge. Typically, the human analyst needs to be\nactively involved during extraction and modeling to resolve\nambiguities that will inevitable arise in such data and to put the\nmodel into context. This paper proposes a visual analytics approach\nthat enables a first intuition and exploration of topics appearing in\nthe text corpus, and facilitates the interactive-iterative refinement\nof the overall topic model describing the stream of tweets. A second\ncontribution is the discussion of efficient graph community detection\nalgorithms to extract initial topics as the starting point of\ninteractive analysis that complement approaches such as LDA. The\napplicability and utility of the proposed approach is shown for\na real-world use case: the analysis of product insights and\ntopic-driven social networks analysis for a specific product line for\nan international hair styling and cosmetics company.<\/jats:p>","DOI":"10.1515\/itit-2014-1078","type":"journal-article","created":{"date-parts":[[2015,1,30]],"date-time":"2015-01-30T12:35:26Z","timestamp":1422621326000},"page":"49-56","source":"Crossref","is-referenced-by-count":1,"title":["A semi-supervised method for topic extraction from micro postings"],"prefix":"10.1515","volume":"57","author":[{"given":"Georg","family":"Fuchs","sequence":"first","affiliation":[{"name":"Fraunhofer IAIS, Sankt Augustin"}]},{"given":"Hendrik","family":"Stange","sequence":"additional","affiliation":[{"name":"Fraunhofer IAIS, Sankt Augustin"}]},{"given":"Ahmad","family":"Samiei","sequence":"additional","affiliation":[{"name":"Fraunhofer IAIS, Sankt Augustin"}]},{"given":"Gennady","family":"Andrienko","sequence":"additional","affiliation":[{"name":"Fraunhofer IAIS, Sankt Augustin"}]},{"given":"Natalia","family":"Andrienko","sequence":"additional","affiliation":[{"name":"Fraunhofer IAIS, Sankt Augustin"}]}],"member":"374","published-online":{"date-parts":[[2015,1,30]]},"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1078\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1078\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T11:43:56Z","timestamp":1624448636000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2014-1078\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,1,30]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,1,30]]},"published-print":{"date-parts":[[2015,2,28]]}},"alternative-id":["10.1515\/itit-2014-1078"],"URL":"https:\/\/doi.org\/10.1515\/itit-2014-1078","relation":{},"ISSN":["1611-2776","2196-7032"],"issn-type":[{"value":"1611-2776","type":"print"},{"value":"2196-7032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1,30]]}}}