{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/32502"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/32502","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Social signaling in decision making","abstract":"Nonverbal communication is an important and often underestimated instrument in social interactions. The paralinguistic elements of speech, which are described in common speech as \"tone of voice\", are one channel of the nonverbal communication. They, together with conversational dynamics, are a very powerful measurement for interactions, without looking at the content of the conversation. A subset of these features, the social signaling measurements, are very useful when analyzing and quantifying conversation. The goal of this thesis is to better understand the framework of social signaling. We applied the social signaling measurements to negotiations as well as to small group interactions. For negotiation we were able to predict up to 30% of the variance in individual outcome. The use of automated algorithms enables to build real-time feedback mechanisms that can then help users to improve and achieve their objectives.","abstract_html":"Nonverbal communication is an important and often underestimated instrument in social interactions. The paralinguistic elements of speech, which are described in common speech as "tone of voice", are one channel of the nonverbal communication. They, together with conversational dynamics, are a very powerful measurement for interactions, without looking at the content of the conversation. A subset of these features, the social signaling measurements, are very useful when analyzing and quantifying conversation. The goal of this thesis is to better understand the framework of social signaling. We applied the social signaling measurements to negotiations as well as to small group interactions. For negotiation we were able to predict up to 30% of the variance in individual outcome. The use of automated algorithms enables to build real-time feedback mechanisms that can then help users to improve and achieve their objectives.","abstract_has_math":false,"creators":["Caneel, Ron"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences","school":null,"contributors":[],"advisors":["Alex P. Pentland and Dan Ariely."],"committee_chairs":[],"committee_members":[],"year":2005,"date_issued":"2005","date_published":"2005","updated_at":"2026-07-22T22:21:29Z","subjects":["Architecture. Program In Media Arts and Sciences"],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/32502","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Alex P. Pentland and Dan Ariely."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Architecture. 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The paralinguistic elements of speech, which are described in common speech as \"tone of voice\", are one channel of the nonverbal communication. They, together with conversational dynamics, are a very powerful measurement for interactions, without looking at the content of the conversation. A subset of these features, the social signaling measurements, are very useful when analyzing and quantifying conversation. The goal of this thesis is to better understand the framework of social signaling. We applied the social signaling measurements to negotiations as well as to small group interactions. For negotiation we were able to predict up to 30% of the variance in individual outcome. 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The goal of this thesis is to better understand the framework of social signaling. We applied the social signaling measurements to negotiations as well as to small group interactions. For negotiation we were able to predict up to 30% of the variance in individual outcome. The use of automated algorithms enables to build real-time feedback mechanisms that can then help users to improve and achieve their objectives."],"dc:description.degree":["S.M."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/32502"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Architecture. 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