Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota
In this study we investigate whether Facebook fan-page posting types and topics have a significant effect on engagement. More specifically, the media type and content theme of posting on Facebook are examined to see whether or not there was a difference between content topics. In order to achieve th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2021-06-01
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| Series: | International Journal of Engineering Business Management |
| Online Access: | https://doi.org/10.1177/18479790211016268 |
| _version_ | 1818621120954236928 |
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| author | Heuiju Chun Byung-Hak Leem Hyesun Suh |
| author_facet | Heuiju Chun Byung-Hak Leem Hyesun Suh |
| author_sort | Heuiju Chun |
| collection | DOAJ |
| description | In this study we investigate whether Facebook fan-page posting types and topics have a significant effect on engagement. More specifically, the media type and content theme of posting on Facebook are examined to see whether or not there was a difference between content topics. In order to achieve this goal, we set hypotheses as follows: (1) the media types of posting have a significant effect on engagement; (2) the topics and sentiment polarity of posting have a significant effect on engagement. We tested these hypotheses using research procedures as follows: (1) collection and preprocessing of social-media data, including posting types, comments, and reactions on Facebook fan pages, (2) topic modeling of fan-page postings using R and SAS, (3) testing hypotheses using a negative binomial regression model, and (4) implications and insights for social-media marketing. Topic modeling applying to textual data and sentiment analysis were conducted. After that, in order to find the factors to affect the number of Facebook fan-page engagements, the negative binomial regression model including post type, topic, sentiment, reactions of “love,” “haha,” and their interaction as exploratory variables was considered. Finally, the results show that post type is the most influential factor to affect social-media engagement, and content topics, sentiments of posts and comments also have significant effects on it. |
| first_indexed | 2024-12-16T18:04:14Z |
| format | Article |
| id | doaj.art-47ca159035164704bb9d0e014f4d7dff |
| institution | Directory Open Access Journal |
| issn | 1847-9790 |
| language | English |
| last_indexed | 2024-12-16T18:04:14Z |
| publishDate | 2021-06-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Engineering Business Management |
| spelling | doaj.art-47ca159035164704bb9d0e014f4d7dff2022-12-21T22:21:57ZengSAGE PublishingInternational Journal of Engineering Business Management1847-97902021-06-011310.1177/18479790211016268Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of ToyotaHeuiju Chun0Byung-Hak Leem1Hyesun Suh2 Department of Statistics and Information, Dongduk Women’s University, Seoul, Korea Department of International Marketing, Busan University of Foreign Studies, Busan, Korea Department of Computer Science Engineering, Daejin University, Pocheon, KoreaIn this study we investigate whether Facebook fan-page posting types and topics have a significant effect on engagement. More specifically, the media type and content theme of posting on Facebook are examined to see whether or not there was a difference between content topics. In order to achieve this goal, we set hypotheses as follows: (1) the media types of posting have a significant effect on engagement; (2) the topics and sentiment polarity of posting have a significant effect on engagement. We tested these hypotheses using research procedures as follows: (1) collection and preprocessing of social-media data, including posting types, comments, and reactions on Facebook fan pages, (2) topic modeling of fan-page postings using R and SAS, (3) testing hypotheses using a negative binomial regression model, and (4) implications and insights for social-media marketing. Topic modeling applying to textual data and sentiment analysis were conducted. After that, in order to find the factors to affect the number of Facebook fan-page engagements, the negative binomial regression model including post type, topic, sentiment, reactions of “love,” “haha,” and their interaction as exploratory variables was considered. Finally, the results show that post type is the most influential factor to affect social-media engagement, and content topics, sentiments of posts and comments also have significant effects on it.https://doi.org/10.1177/18479790211016268 |
| spellingShingle | Heuiju Chun Byung-Hak Leem Hyesun Suh Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota International Journal of Engineering Business Management |
| title | Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota |
| title_full | Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota |
| title_fullStr | Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota |
| title_full_unstemmed | Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota |
| title_short | Using text analytics to measure an effect of topics and sentiments on social-media engagement: Focusing on Facebook fan page of Toyota |
| title_sort | using text analytics to measure an effect of topics and sentiments on social media engagement focusing on facebook fan page of toyota |
| url | https://doi.org/10.1177/18479790211016268 |
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