{"id":334817,"date":"2016-12-11T14:13:06","date_gmt":"2016-12-11T22:13:06","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=334817"},"modified":"2018-10-16T20:05:50","modified_gmt":"2018-10-17T03:05:50","slug":"brain-facebook-neuropsychological-associations-social","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/brain-facebook-neuropsychological-associations-social\/","title":{"rendered":"Your Brain on Facebook: Neuropsychological Associations with Social"},"content":{"rendered":"

We measured individuals\u2019 mental associations between four types of media (books, television, social\/Facebook, and general informational web pages) and relevant concepts (Addictive, Story, Interesting, Frivolous, Personal, and Useful) using three different measurements: a Likert scale questionnaire, a speeded Yes\/No judgment task, and electrical brain activity. The three measures were designed to capture associations at different levels of mental processing, from very automatic (electrical brain activity) to conscious and reasoned (questionnaire). At more conscious levels of cognitive processing, Facebook was seen as interesting, addictive, and highly personal. Results for the electrical brain activity measure show that Facebook tells less of a story and, surprisingly, is less personal than other forms of media. We discuss differences in results across the three measures and how our findings can inform the design of future social media systems.<\/p>\n","protected":false},"excerpt":{"rendered":"

We measured individuals\u2019 mental associations between four types of media (books, television, social\/Facebook, and general informational web pages) and relevant concepts (Addictive, Story, Interesting, Frivolous, Personal, and Useful) using three different measurements: a Likert scale questionnaire, a speeded Yes\/No judgment task, and electrical brain activity. The three measures were designed to capture associations at different […]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-334817","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Conference: Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM 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