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dc.contributor.authorIlina, Elenaen
dc.contributor.authorAbel, Fabianen
dc.contributor.authorHouben, Geert-Janen
dc.contributor.editorAugstein, Mirjamen
dc.contributor.editorHeckmann, Dominiken
dc.contributor.editorHerder, Eelcoen
dc.date.accessioned2017-11-15T15:01:28Z
dc.date.available2017-11-15T15:01:28Z
dc.date.issued2012
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/5116
dc.description.abstractAdaptive applications rely on the knowledge of their users, their needs and differences. For instance, in the scope of the ImReal 1 project, a training process is adapted to users’ origins using information on user cultural backgrounds. For inferring culture-specific information from available microblogging content, we monitor the usage of Twitter elements such as hashtags, web links and user mentions. We analyze how users from different cultural groups employ these elements when they tweet. This allows us to get insights on microblogging patterns for different cultural groups of Twitter users and an outlook into user preferences and traits towards sharing content with others, time preferences, and social networking attitudes. Potentially, such information can be used for adapting software applications in accord with user culture-specific behavioral traits.en
dc.language.isoenen
dc.relation.ispartofABIS 2012de_DE
dc.subjectMining Twitteren
dc.titleMining Twitter for Cultural Patternsen
dc.typeworkshopde_DE
dc.pubPlaceKonstanzde_DE
mci.document.qualitydigidocen


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