{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/46017"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/46017","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Social media analytics in business intelligence applications","abstract":"Social media is becoming increasingly important in society and culture, empowering consumers to group together on common interests and share opinions through the Internet. The social web shifts the originators of content from companies to users. Differences caused by this dynamic result in existing web analytic techniques being inadequate. Because people reveal their thoughts and preferences in social media, there are significant opportunities in business intelligence by analyzing social media. These opportunities include brand monitoring; trend recognition, and targeted advertising. The market for social media analytics in business intelligence is further validated by its direct application in the consumer research market. Challenges lie ahead for development and adoption of social media analytics. Technology used in these analytics, such as natural language processing and social network analysis, need to mature to improve accuracy, performance, and scalability. Nevertheless, social media continues to grow at a rapid pace, and organizations should form strategies to incorporate social media analytics into their business intelligence frameworks.","abstract_html":"Social media is becoming increasingly important in society and culture, empowering consumers to group together on common interests and share opinions through the Internet. The social web shifts the originators of content from companies to users. Differences caused by this dynamic result in existing web analytic techniques being inadequate. Because people reveal their thoughts and preferences in social media, there are significant opportunities in business intelligence by analyzing social media. These opportunities include brand monitoring; trend recognition, and targeted advertising. The market for social media analytics in business intelligence is further validated by its direct application in the consumer research market. Challenges lie ahead for development and adoption of social media analytics. Technology used in these analytics, such as natural language processing and social network analysis, need to mature to improve accuracy, performance, and scalability. Nevertheless, social media continues to grow at a rapid pace, and organizations should form strategies to incorporate social media analytics into their business intelligence frameworks.","abstract_has_math":false,"creators":["Lo, Bobby"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Michael A. Cusumano."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:34Z","subjects":["Electrical Engineering and Computer Science."],"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/1721.1/46017","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Michael A. Cusumano."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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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."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/46017"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.","Includes bibliographical references (p. 89-93)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Social media is becoming increasingly important in society and culture, empowering consumers to group together on common interests and share opinions through the Internet. The social web shifts the originators of content from companies to users. Differences caused by this dynamic result in existing web analytic techniques being inadequate. Because people reveal their thoughts and preferences in social media, there are significant opportunities in business intelligence by analyzing social media. These opportunities include brand monitoring; trend recognition, and targeted advertising. The market for social media analytics in business intelligence is further validated by its direct application in the consumer research market. Challenges lie ahead for development and adoption of social media analytics. Technology used in these analytics, such as natural language processing and social network analysis, need to mature to improve accuracy, performance, and scalability. Nevertheless, social media continues to grow at a rapid pace, and organizations should form strategies to incorporate social media analytics into their business intelligence frameworks."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["Social media analytics in business intelligence applications"]}]}],"canonical_facts":{"dc:contributor.advisor":["Michael A. Cusumano."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:creator":["Lo, Bobby"],"dc:date.accessioned":["2009-06-30T17:01:49Z"],"dc:date.available":["2009-06-30T17:01:49Z"],"dc:date.issued":["2008"],"dc:description":["Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.","Includes bibliographical references (p. 89-93)."],"dc:description.abstract":["Social media is becoming increasingly important in society and culture, empowering consumers to group together on common interests and share opinions through the Internet. The social web shifts the originators of content from companies to users. Differences caused by this dynamic result in existing web analytic techniques being inadequate. Because people reveal their thoughts and preferences in social media, there are significant opportunities in business intelligence by analyzing social media. These opportunities include brand monitoring; trend recognition, and targeted advertising. The market for social media analytics in business intelligence is further validated by its direct application in the consumer research market. Challenges lie ahead for development and adoption of social media analytics. Technology used in these analytics, such as natural language processing and social network analysis, need to mature to improve accuracy, performance, and scalability. Nevertheless, social media continues to grow at a rapid pace, and organizations should form strategies to incorporate social media analytics into their business intelligence frameworks."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/46017"],"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":["Electrical Engineering and Computer Science."],"dc:title":["Social media analytics in business intelligence applications"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:34Z"}