Mining personal media thresholds for opinion dynamics and social influence

To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data...

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Vydané v:Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining s. 1258 - 1265
Hlavní autori: Doyle, Casey, Meandzija, Alex, Korniss, Gyorgy, Szymanski, Boleslaw, Asher, Derrik, Bowman, Elizabeth
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Piscataway, NJ, USA IEEE Press 28.08.2018
Edícia:ACM Conferences
Predmet:
Information systems
Information systems > Information systems applications
Information systems > Information systems applications > Data mining
association rules
personal influence thresholds
crowdsourcing
social media
data mining
opinion formation
ISBN:1538660512, 9781538660515
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Abstract To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data for common groupings of responses with respect to various media types, sources, and contexts. We show that in general individuals tend to perceive their behavior to be consistent across many variations in these parameters, while further detail shows various common parameter groupings that indicate response changes as well as small groups of individuals that tend to be consistently more easily swayed than the average participant.
AbstractList To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data for common groupings of responses with respect to various media types, sources, and contexts. We show that in general individuals tend to perceive their behavior to be consistent across many variations in these parameters, while further detail shows various common parameter groupings that indicate response changes as well as small groups of individuals that tend to be consistently more easily swayed than the average participant.
Author Szymanski, Boleslaw
Korniss, Gyorgy
Asher, Derrik
Meandzija, Alex
Doyle, Casey
Bowman, Elizabeth
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Editor Brandes, Ulrik
Tagarelli, Andrea
Reddy, Chandan
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  organization: University of Calabria, Italy
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Keywords association rules
personal influence thresholds
crowdsourcing
social media
data mining
opinion formation
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Snippet To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media...
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SubjectTerms Information systems
Information systems -- Information systems applications
Information systems -- Information systems applications -- Data mining
Title Mining personal media thresholds for opinion dynamics and social influence
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