Perceptions of presidential candidates' personalities in twitter
Political sentiment analysis using social media, especially Twitter, has attracted wide interest in recent years. In such research, opinions about politicians are typically divided into positive, negative, or neutral. In our research, the goal is to mine political opinion from social media at a high...
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Published in | Journal of the Association for Information Science and Technology Vol. 67; no. 2; pp. 249 - 267 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Blackwell Publishing Ltd
01.02.2016
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Subjects | |
Online Access | Get full text |
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Abstract | Political sentiment analysis using social media, especially Twitter, has attracted wide interest in recent years. In such research, opinions about politicians are typically divided into positive, negative, or neutral. In our research, the goal is to mine political opinion from social media at a higher resolution by assessing statements of opinion related to the personality traits of politicians; this is an angle that has not yet been considered in social media research. A second goal is to contribute a novel retrieval‐based approach for tracking public perception of personality using Gough and Heilbrun's Adjective Check List (ACL) of 110 terms describing key traits. This is in contrast to the typical lexical and machine‐learning approaches used in sentiment analysis. High‐precision search templates developed from the ACL were run on an 18‐month span of Twitter posts mentioning Obama and Romney and these retrieved more than half a million tweets. For example, the results indicated that Romney was perceived as more of an achiever and Obama was perceived as somewhat more friendly. The traits were also aggregated into 14 broad personality dimensions. For example, Obama rated far higher than Romney on the Moderation dimension and lower on the Machiavellianism dimension. The temporal variability of such perceptions was explored. |
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AbstractList | Political sentiment analysis using social media, especially Twitter, has attracted wide interest in recent years. In such research, opinions about politicians are typically divided into positive, negative, or neutral. In our research, the goal is to mine political opinion from social media at a higher resolution by assessing statements of opinion related to the personality traits of politicians; this is an angle that has not yet been considered in social media research. A second goal is to contribute a novel retrieval‐based approach for tracking public perception of personality using Gough and Heilbrun's Adjective Check List (ACL) of 110 terms describing key traits. This is in contrast to the typical lexical and machine‐learning approaches used in sentiment analysis. High‐precision search templates developed from the ACL were run on an 18‐month span of Twitter posts mentioning Obama and Romney and these retrieved more than half a million tweets. For example, the results indicated that Romney was perceived as more of an achiever and Obama was perceived as somewhat more friendly. The traits were also aggregated into 14 broad personality dimensions. For example, Obama rated far higher than Romney on the Moderation dimension and lower on the Machiavellianism dimension. The temporal variability of such perceptions was explored. Political sentiment analysis using social media, especially T witter, has attracted wide interest in recent years. In such research, opinions about politicians are typically divided into positive, negative, or neutral. In our research, the goal is to mine political opinion from social media at a higher resolution by assessing statements of opinion related to the personality traits of politicians; this is an angle that has not yet been considered in social media research. A second goal is to contribute a novel retrieval‐based approach for tracking public perception of personality using G ough and H eilbrun's A djective C heck List ( ACL ) of 110 terms describing key traits. This is in contrast to the typical lexical and machine‐learning approaches used in sentiment analysis. High‐precision search templates developed from the ACL were run on an 18‐month span of T witter posts mentioning O bama and R omney and these retrieved more than half a million tweets. For example, the results indicated that R omney was perceived as more of an achiever and O bama was perceived as somewhat more friendly. The traits were also aggregated into 14 broad personality dimensions. For example, O bama rated far higher than R omney on the M oderation dimension and lower on the M achiavellianism dimension. The temporal variability of such perceptions was explored. |
Author | Boynton, Bob Yang, Chao Srinivasan, Padmini Bhattacharya, Sanmitra |
Author_xml | – sequence: 1 givenname: Sanmitra surname: Bhattacharya fullname: Bhattacharya, Sanmitra email: sanmitra-bhattacharya@uiowa.edu organization: Department of Computer Science, The University of Iowa, 14 MacLean Hall, IA, 52242, Iowa City – sequence: 2 givenname: Chao surname: Yang fullname: Yang, Chao email: chao-yang@uiowa.edu organization: Department of Computer Science, The University of Iowa, 14 MacLean Hall, IA, 52242, Iowa City – sequence: 3 givenname: Padmini surname: Srinivasan fullname: Srinivasan, Padmini email: padmini-srinivasan@uiowa.edu organization: Department of Computer Science, The University of Iowa, 14 MacLean Hall, IA, 52242, Iowa City – sequence: 4 givenname: Bob surname: Boynton fullname: Boynton, Bob email: bob-boynton@uiowa.edu organization: Department of Political Science, The University of Iowa, 341 Schaeffer Hall, IA, 52242, Iowa City |
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SubjectTerms | Data mining Digital media information retrieval Lists Perception Personality Searching Social networks text mining Tracking web mining |
Title | Perceptions of presidential candidates' personalities in twitter |
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