We analyze the relation between user interests and their perceived psychodemographic\u00a0attributes using Twitter data, training models for predicting\u00a0various personal traits of users. In contrast to existing work, which bases\u00a0predictions on the textual tweets produced by users, we leverage the fact that\u00a0users are embedded in the Twitter social network.\u00a0We examine the accounts that our users follow, and use them to determine\u00a0the high-level interests of these users, then use these areas of interest as\u00a0features for predicting perceived personal traits. We cover target attributes\u00a0such as gender, age, educational background, political stand and personality.\u00a0We evaluate our technique on a dataset of over 4,000 Twitter user\u00a0profiles. We use crowdsourcing to annotate these user profiles with perceptions\u00a0regarding their personal traits, and correlate these with user interests, as\u00a0captured by the accounts they follow and their classification in the Twitter\u00a0\u201cWho To Follow\u201d hierarchy.\u00a0We compare the accuracy of our personal trait prediction methods with\u00a0the state-of-the-art approaches that solely rely on user tweets, and discuss the\u00a0correlations between perceived user demographics and interests.<\/p>\n","protected":false},"excerpt":{"rendered":"
We analyze the relation between user interests and their perceived psychodemographic\u00a0attributes using Twitter data, training models for predicting\u00a0various personal traits of users. In contrast to existing work, which bases\u00a0predictions on the textual tweets produced by users, we leverage the fact that\u00a0users are embedded in the Twitter social network.\u00a0We examine the accounts that our users follow, […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"IEEE","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"IEEE Big Data Service 2016","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"IEEE Big Data Service 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