Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies
Purpose: The aim of this article was to identify differences in the emotional tone of verbal messages published on the Facebook accounts of selected companies within the fashion industry, focusing on organizations with an active presence on this platform. Design/methodology/approach: The sentimen...
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| Format: | Article |
| Language: | English |
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University of Warsaw
2024-12-01
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| Series: | European Management Studies |
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| Online Access: | https://press.wz.uw.edu.pl/ems/vol22/iss3/1 |
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| author | Karolina Mania Monika Jedynak Aneta Kuźniarska Karolina Woszczyna |
| author_facet | Karolina Mania Monika Jedynak Aneta Kuźniarska Karolina Woszczyna |
| author_sort | Karolina Mania |
| collection | DOAJ |
| description | Purpose: The aim of this article was to identify differences in the emotional tone of verbal messages published on the Facebook accounts of selected companies within the fashion industry, focusing on organizations with an active presence on this platform.
Design/methodology/approach: The sentiment analysis was conducted using the CLARIN software suite. Over a three-month period in 2023, companies’ posts and users’ comments were collected and analyzed. Sentiments were categorized into six groups: ambiguous statements, strong and weak negative statements, strong and weak positive statements, and neutral statements. Analysis was performed at sentence, document, and aspect levels, employing both lexicon-based methods and machine learning.
Findings: The results showed a preponderance of strong positive sentiment among the messages seen on the social media channels of the companies analyzed.
Research limitations/implications: The study was limited to a three-month data collection period and focused exclusively on organizations within the fashion industry with an active Facebook presence, which may limit the generalizability of the findings to other industries or platforms.
Originality/value: This study contributes to the understanding of how corporate communication on social media impacts its users, offering insights specifically into sentiment dynamics within the fashion industry. |
| format | Article |
| id | doaj-art-be70d55cc4fb42c2bffd249da7368899 |
| institution | Kabale University |
| issn | 2956-7602 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | University of Warsaw |
| record_format | Article |
| series | European Management Studies |
| spelling | doaj-art-be70d55cc4fb42c2bffd249da73688992025-02-07T12:25:09ZengUniversity of WarsawEuropean Management Studies2956-76022024-12-012024342110.7172/2956-7602.105.1Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion CompaniesKarolina Mania0https://orcid.org/0000-0001-9063-7563Monika Jedynak1https://orcid.org/0000-0002-0167-5013Aneta Kuźniarska2https://orcid.org/0000-0002-2786-2781Karolina Woszczyna3https://orcid.org/0000-0001-6575-3669Institute of Economics, Finance and Management, Faculty of Management and Social Communication, Jagiellonian University, PolandInstitute of Economics, Finance and Management, Faculty of Management and Social Communication, Jagiellonian University, PolandInstitute of Economics, Finance and Management, Faculty of Management and Social Communication, Jagiellonian University, PolandInstitute of Economics, Finance and Management, Faculty of Management and Social Communication, Jagiellonian University, PolandPurpose: The aim of this article was to identify differences in the emotional tone of verbal messages published on the Facebook accounts of selected companies within the fashion industry, focusing on organizations with an active presence on this platform. Design/methodology/approach: The sentiment analysis was conducted using the CLARIN software suite. Over a three-month period in 2023, companies’ posts and users’ comments were collected and analyzed. Sentiments were categorized into six groups: ambiguous statements, strong and weak negative statements, strong and weak positive statements, and neutral statements. Analysis was performed at sentence, document, and aspect levels, employing both lexicon-based methods and machine learning. Findings: The results showed a preponderance of strong positive sentiment among the messages seen on the social media channels of the companies analyzed. Research limitations/implications: The study was limited to a three-month data collection period and focused exclusively on organizations within the fashion industry with an active Facebook presence, which may limit the generalizability of the findings to other industries or platforms. Originality/value: This study contributes to the understanding of how corporate communication on social media impacts its users, offering insights specifically into sentiment dynamics within the fashion industry.https://press.wz.uw.edu.pl/ems/vol22/iss3/1social mediacommunicationsentiment analysisfacebook |
| spellingShingle | Karolina Mania Monika Jedynak Aneta Kuźniarska Karolina Woszczyna Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies European Management Studies social media communication sentiment analysis |
| title | Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies |
| title_full | Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies |
| title_fullStr | Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies |
| title_full_unstemmed | Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies |
| title_short | Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies |
| title_sort | decoding sentiment in online communication a social media analysis of fashion companies |
| topic | social media communication sentiment analysis |
| url | https://press.wz.uw.edu.pl/ems/vol22/iss3/1 |
| work_keys_str_mv | AT karolinamania decodingsentimentinonlinecommunicationasocialmediaanalysisoffashioncompanies AT monikajedynak decodingsentimentinonlinecommunicationasocialmediaanalysisoffashioncompanies AT anetakuzniarska decodingsentimentinonlinecommunicationasocialmediaanalysisoffashioncompanies AT karolinawoszczyna decodingsentimentinonlinecommunicationasocialmediaanalysisoffashioncompanies |