Computerized emotional content analysis: empirical findings based on charity social media advertisements. Kwon, J., Lin, H., Deng, L., Dellicompagni, T., & Kang, M. Y. INTERNATIONAL JOURNAL OF ADVERTISING, 41(7):1314–1337, September, 2022. Place: 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND Publisher: ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD Type: Articledoi abstract bibtex There has been a long debate about effective emotional appeals on charity advertisements. While many charity organizations recently shifted from negative emotions to happy emotions on their social media, it is not clearly proven whether this strategy is more effective. The objective of this study is to find more detailed unknown information to optimally use emotional charity advertisements on social media. We investigate the effect of 1) emotional valence, 2) their match between images and textual descriptions, 3) their length, and 4) their post timing on social media engagement. By automatically extracting emotions expressed both in facial images and textual descriptions from 3,066 charity posts from Save the Children's official Instagram account using the computerized emotional content analysis, we provide findings on what, how much, when, and how charity managers can come up with a clear configuration for their social media advertisements.
@article{kwon_computerized_2022,
title = {Computerized emotional content analysis: empirical findings based on charity social media advertisements},
volume = {41},
issn = {0265-0487},
doi = {10.1080/02650487.2021.2012070},
abstract = {There has been a long debate about effective emotional appeals on charity advertisements. While many charity organizations recently shifted from negative emotions to happy emotions on their social media, it is not clearly proven whether this strategy is more effective. The objective of this study is to find more detailed unknown information to optimally use emotional charity advertisements on social media. We investigate the effect of 1) emotional valence, 2) their match between images and textual descriptions, 3) their length, and 4) their post timing on social media engagement. By automatically extracting emotions expressed both in facial images and textual descriptions from 3,066 charity posts from Save the Children's official Instagram account using the computerized emotional content analysis, we provide findings on what, how much, when, and how charity managers can come up with a clear configuration for their social media advertisements.},
language = {English},
number = {7},
journal = {INTERNATIONAL JOURNAL OF ADVERTISING},
author = {Kwon, Junbum and Lin, Hanyi and Deng, Lichen and Dellicompagni, Tanya and Kang, Moon Young},
month = sep,
year = {2022},
note = {Place: 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
Publisher: ROUTLEDGE JOURNALS, TAYLOR \& FRANCIS LTD
Type: Article},
keywords = {Charity emotion advertisement, computerized automatic emotional content analysis, emotional match, emotional valence, multi-modal content analysis, post timing, social media, text length by emotional type},
pages = {1314--1337},
}
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We investigate the effect of 1) emotional valence, 2) their match between images and textual descriptions, 3) their length, and 4) their post timing on social media engagement. 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