Social media as a medium of word-of-mouth - Investigating movie eWOM dynamics using Tweets

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dc.contributor Aalto University en
dc.contributor Aalto-yliopisto fi
dc.contributor.author Laurila, Jaakko
dc.date.accessioned 2011-11-14T11:23:41Z
dc.date.available 2011-11-14T11:23:41Z
dc.date.issued 2010
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/562
dc.description.abstract RESEARCH OBJECTIVES The objective of this thesis is to explore the field of electronic word-of-mouth in social media and to provide insight how companies can aggregate, analyze and utilize WOM data collected from social media services. The topic was approached with an introduction to past WOM research and an examination of how it is transmitted in different social media services. Finally, eWOM dynamics were studied in the context of Hollywood movies using real word-of-mouth data collected from microblogging service Twitter. DATA AND METHODOLOGY A program was written to collect status updates mentioning a specified Hollywood movie title from Twitter. Data collection started two days before premiere and lasted until the end of second weekend. Two eWOM attributes were measured: volume – the amount of WOM that comes about, and valence – the measure of opinion expressed in the message. To take into account the unique characteristics of Twitter updates, the data was preprocessed to improve the data quality. RESULTS The main findings show that movie eWOM volume and box office sales figures are highly correlated. They form a feedback system, both impacting each other. Both volume and sales are highest in the first two weekends highlighting the importance of pre-release marketing. Valence seems to rather static during the measurement period, but more positive than negative. The uniqueness of Twitter data requires customized text mining application to get more accurate valence analysis. en
dc.format.extent 73
dc.language.iso en en
dc.title Social media as a medium of word-of-mouth - Investigating movie eWOM dynamics using Tweets en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Kauppakorkeakoulu fi
dc.contributor.school School of Economics en
dc.contributor.department Department of Business Technology en
dc.contributor.department Liiketoiminnan teknologian laitos fi
dc.subject.keyword Word-of-mouth
dc.subject.keyword social media
dc.subject.keyword Twitter
dc.subject.keyword text mining
dc.subject.keyword sentiment analysis
dc.identifier.urn URN:NBN:fi:aalto-201111181474
dc.type.dcmitype text en
dc.programme.major Information Systems Science en
dc.programme.major Tietojärjestelmätiede fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Pro gradu tutkielma fi
dc.subject.helecon tietojärjestelmät
dc.subject.helecon information systems
dc.subject.helecon sosiaalinen media
dc.subject.helecon social media
dc.subject.helecon viestintä
dc.subject.helecon communication
dc.subject.helecon markkinointi
dc.subject.helecon marketing
dc.ethesisid 12430
dc.date.dateaccepted 0010-06-18
dc.location P1 I


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