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Utilizing this data, social networks can be derived and analyzed to detect influential users and opinion tendencies. The approach is applied to sample online forums discussing the iPhone.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Combining text mining and social network analysis enables the study of opinion formation and yields encouraging results. Out of the four methods employed for text mining, support vector machines performed best.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The data set applied here is fairly small. More threads on different products will be considered in future work to improve validation.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The approach represents a valuable instrument for online market research. It enables companies to recognize opportunities and risks and to initiate appropriate marketing actions.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>This work is one of the first studies that combine communication content, relationships and dialog acts for analyzing opinion formation.<\/jats:p><\/jats:sec>","DOI":"10.1108\/10662241211235653","type":"journal-article","created":{"date-parts":[[2014,5,9]],"date-time":"2014-05-09T06:04:45Z","timestamp":1399615485000},"page":"275-297","source":"Crossref","is-referenced-by-count":33,"title":["Mining consumer dialog in online forums"],"prefix":"10.1108","volume":"22","author":[{"given":"Carolin","family":"Kaiser","sequence":"first","affiliation":[]},{"given":"Freimut","family":"Bodendorf","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022012120205663800_b1","unstructured":"Adar, E. and Adamic, L.A. 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