{"id":334916,"date":"2016-12-11T17:23:30","date_gmt":"2016-12-12T01:23:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=334916"},"modified":"2018-10-16T20:06:26","modified_gmt":"2018-10-17T03:06:26","slug":"sounds-good-effects-photo-voice-profiles-gamer-partner-choice","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/sounds-good-effects-photo-voice-profiles-gamer-partner-choice\/","title":{"rendered":"Sounds Good to Me: Effects of Photo and Voice Profiles on Gamer Partner Choice"},"content":{"rendered":"

In an empirical study we investigated how matchmaking for online gaming platforms could benefit from additional implicit information conveyed in profiles that include photos or voice recordings. We used 150 real online gamer profiles (50 text-only, 50 text & photo, 50 text & voice) to elicit gaming partner preferences from 267 online gamers. We found profiles with photos to lead to lower overall preference, indicating that people used them to reject potential partners. Voice recordings did not reduce overall preference but gave participants relevant information for gaming partner choice. We close with recommendations for the design of online profiles.<\/p>\n","protected":false},"excerpt":{"rendered":"

In an empirical study we investigated how matchmaking for online gaming platforms could benefit from additional implicit information conveyed in profiles that include photos or voice recordings. We used 150 real online gamer profiles (50 text-only, 50 text & photo, 50 text & voice) to elicit gaming partner preferences from 267 online gamers. We found […]<\/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-334916","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work","msr_affiliation":"","msr_published_date":"2006-11-04","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"159-162","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"334919","msr_publicationurl":"","msr_doi":"10.1145\/1180875.1180899","msr_publication_uploader":[{"type":"file","title":"sounds_good_to_me","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/12\/sounds_good_to_me.pdf","id":334919,"label_id":0},{"type":"doi","title":"10.1145\/1180875.1180899","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Jens Riegelsberger","user_id":0,"rest_url":false},{"type":"user_nicename","value":"counts","user_id":31471,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=counts"},{"type":"text","value":"Shelly D. Farnham","user_id":0,"rest_url":false},{"type":"text","value":"Bruce C. 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