Analysis of Twitter User Responses to the Aqua Billboards Series #DiRumahAJa

Authors

DOI:

https://doi.org/10.12928/channel.v10i1.22332

Keywords:

advertisement, Twitter, Sentiment Analysis

Abstract

Advertising is a marketing communication to promote or sell a product with several purposes and characteristics. There are two characteristics of it, commercial and non-commercial advertising, such as public service advertisement. Public service advertisement aims to inform a message of public importance. A mineral water company, AQUA, has made a public service advertisement about Covid-19. AQUA use billboard as the media to inform message to the public. This billboard has been a hot topic on social media, especially on Twitter. The aftermath of this billboard is incredible. Users on Twitter do interact with this billboard picture. This research aims to analyze users' sentiment about this billboard. The author uses a descriptive qualitative method in this research. The author collects the data from Twitter directly, taking a screenshot of each user's response to the billboard picture. The author collects all responses and categorizes the responses into positive, negative, and neutral. The author uses a programming language, Python, to obtain a graphic for research needs, and the result is analyzed with Sentiment Analysis theory. The result shows that positive responses are more significant with 73.2%.

Author Biographies

Agy Firda Sandi, Universitas Ahmad Dahlan

Communication Department

Arif Ardy Wibowo, University Ahmad Dahlan

Communication Department

Rahina Nugrahani, Universitas Negeri Semarang

Visual Communication Design Department

Roziani Mohd Nasir, Universiti Teknologi MARA Kelantan

 Faculty of Art & Design 

References

Atteveldt, W. Van., Velden, M. A. C. G. van der and Boukes, M. (2021). "The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms," Commun. Methods Meas., 15(2), pp. 121–140, 2021, DOI: 10.1080/19312458.2020.1869198.

Batubara, Abdul Karim. (2014). "Media Ecology Theory," J. Iqra', vol. 08, no. 02, pp. 133–146

Chintalapudi, N., Battineni, G., Di Canio, M., Sagaro, G. G. and Amenta, F. (2021). "Text Mining With Sentiment Analysis On Seafarers' Medical Documents," Int. J. Inf. Manag. Data Insights, 1(1), p. 100005, 2021, DOI: 10.1016/j.jjimei.2020.100005.

D'Andrea, A. Ferri, F., Grifoni, P. and Guzzo, T. (2015). "Approaches, Tools, and Applications for Sentiment Analysis Implementation," Int. J. Comput. A pl., 125(3), pp. 26–33, DOI: 10.5120/ijca2015905866.

Ikasari, D., Fajarwati, Y., and Widiastuti. (2020) “Analisis Sentimen Dan Klasifikasi Tweets Berbahasa Indonesia Terhadap Transportasi Umum Mrt Jakarta Menggunakan Naïve Bayes Classifier,” J. Ilm. Inform. Komput., 25(1), pp. 64–75, 2020, doi: 10.35760/ik.2020.v25i1.2427.

Jiang, Q., Chan, C. S., Eichelberger, S. Ma, H. and Pikkemaat, B. (2021). "Sentiment analysis of online destination image of Hong Kong held by mainland Chinese tourists," Curr. Issues Tour., 24(17), pp. 2501–2522 DOI: 10.1080/13683500.2021.1874312.

Kasatriyanto, B., Wibowo, A. A., and Mat Nashir, R. B. (2021). "Video Podcast As Alternative Education Media of Borobudur Temple Campaign During Pandemic Covid-19," Int. J. Commun. S c., 3(2), pp. 130–139, [Online]. Available: http://pubs2.ascee.org/index.php/IJCSIJCS@ascee.org

Kriyantono, R. (2013). Manajemen Periklanan: Teori dan Praktik. Malang: Universitas Brawijaya Press

Leavy, P. (2017). "Research Design: Quantitative, Qualitative, Mixed Methods, Arts-Based, and Community-Based Participatory Research Approaches," vol. 91, pp. 1–320, DOI: 10.1017/CBO9781107415324.004.

Li, H., Chen, Q., Zhong, Z., Gong, R., and Han, G. (2022). "E-Word Of Mouth Sentiment Analysis For User Behavior Studies," Inf. Process. Manag., vol. 59, no. 1, p. 102784, 2022, DOI: 10.1016/j.ipm.2021.102784.

Liu, S., and Liu, J. (2021). "Public Attitudes Toward COVID-19 Vaccines On English-Language Twitter: A Sentiment Analysis," Vaccine, 39(39), pp. 5499–5505, 2021, DOI: 10.1016/j.vaccine.2021.08.058.

Liu, B. (2012). Sentiment Analysis and Opinion Mining. Toronto: Morgan & Claypool

McLuhan, M. (2013). Understanding Media: the extensions of man, 3rd ed. California: Gingko Press,. doi: 10.1017/CBO9781107415324.004.

Ratana, M. (2018). "The Effect of Social Media Marketing on Brand Equity (Photo Crowdsourcing Program from)," J. Stud. Komun. Dan Media, vol. 22, no. 1, pp. 13–28, 2018, DOI: http://dx.doi.org/10.31445/jskm.2018.220102.

Sutherland, W., and Jarrahi, M. H. (2018). "The Sharing Economy And Digital Platforms: A Review And Research Agenda," Int. J. Inf. Manage., 43. February, pp. 328–341, 2018, DOI: 10.1016/j.ijinfomgt.2018.07.004.

West, R., and Turner, L. H. (2017). Introducing Communication Theory Analysis And Application, 6th ed. New York: McGraw-Hill

Downloads

Published

2022-04-15

Issue

Vol. 10 No. 1 (2022)

Section

Articles

License

Authors submitting a manuscript do so on the understanding that if accepted for publication, the article's copyright shall be assigned to Channel Jurnal Komunikasi.

Authors should sign the Copyright Transfer Agreement when they have approved the final proofs sent by Channel Jurnal Komunikasi before the publication. Channel Jurnal Komunikasi strives to ensure that no errors occur in the articles that have been published, both data errors and statements in the article.

Channel Jurnal Komunikasi keeps the rights to articles that have been published. Authors are permitted to disseminate published articles by sharing the Channel Jurnal Komunikasi website link. Authors are allowed to use their works for any purposes deemed necessary without written permission from Channel Jurnal Komunikasi to acknowledge initial publication in this journal.

All articles published in Channel Jurnal Komunikasi are licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA) license.