Sentiments Analysis on Twitter Towards Hoax Information on Social Media News

Ansar Suherman, Ferdi Ferdi, Harry Fajar Maulana, Muhammad Rizal Ardiansah Putra

Abstract


Hoaxes are a perilous byproduct of huge technology advancements, particularly the rise of social media. Using Twitter as an example, it is one of the most popular social media platforms for information sharing, communication, and entertainment. As a consequence, Twitter users may readily propagate fake or hoax information. The aim of this study is to find public opinion about hoaxes derived from Twitter user conversations around COVID-19. This study makes use of Twitter data obtained from Drone Emprit Academic. This study examined all processed tweets and surveyed public opinion on "Hoaks" (including mentions, retweets, and replies). The DEA engine analyzes the word frequency and mood of Twitter users to determine if a predominant emotion is good, negative, or neutral. According to the study results, netizens remarked on the COVID-19, alleging that the appearance of the Delta type variation was caused by the vaccination, not the virus. They do not regularly check facts owing to boredom, laziness, and reliance on just one source of information verification. Furthermore, only information that corresponds to their interests and needs will be approved. Thus, via discourse about Hoax, social media allows the formation of a platform for mutual understanding, sharing, and dynamically debating the meaning of demonstrations. This research provides a contribution to the disclosure of information about public opinion towards a discourse discussed on Twitter with the help of a DEA engine.


Keywords


sentiments analysis; Hoax; Twitter; infodemic

Full Text:

PDF

References


. Profesional de La Informacion, 30(4). https://doi.org/10.3145/epi.2021.jul.12

Chahine, S., & Malhotra, N. K. (2018). Impact of social media strategies on stock price: the case of Twitter. European Journal of Marketing, 52(7–8), 1526–1549. https://doi.org/10.1108/EJM-10-2017-0718

DEMIR, H. (2020). Dissent and Activism during the Gezi Park Protest: The Role of Social Media in Advocating the Right to Public Space and Democracy. Journal of Global Social Sciences.

Fahmi, I. (2018). Drone Emprit Academic: Software for social media monitoring and analytics. In Drone Emprit Academic.

Fardiah, D., Darmawan, F., & Rinawati, R. (2022). Fact-checking Literacy of Covid-19 Infodemic on Social Media in Indonesia. Komunikator, 14(1), 14–29. https://doi.org/10.18196/jkm.14459

Finneman, T., & Thomas, R. J. (2018). A family of falsehoods: Deception, media hoaxes and fake news. Newspaper Research Journal, 39(3), 350–361. https://doi.org/10.1177/0739532918796228

García-Orosa, B. (2021). Disinformation, social media, bots, and astroturfing: the fourth wave of digital democracy. Profesional de La Informacion, 30(6). https://doi.org/10.3145/epi.2021.nov.03

Helberger, N., Van Drunen, M., Eskens, S., Bastian, M., & Moeller, J. (2020). A freedom of expression perspective on AI in the media-with a special focus on editorial decision making on social media platforms and in the news media. European Journal of Law and Technology, 11(3).

Hesthi Rahayu, W., & Utari, P. (2018). Elaborasi Pesan Hoax Di Grup Facebook Info Wong Solo. Komunikator, 10(1), 24–33. https://doi.org/10.18196/jkm.101003

Hidayat, T., & Mahardiko, R. (2020). The effect of social media regulatory content law in Indonesia. Journal of Telecommunications and the Digital Economy, 8(2), 110–122. https://doi.org/10.18080/jtde.v8n2.247

Hudoch, A. (1999). The Role of Media in Democracy. In Center for Democracy and Governance (Issue June, p. 48). ijrar.org.

Inwood, O., & Zappavigna, M. (2021). Ambient affiliation, misinformation and moral panic: Negotiating social bonds in a YouTube internet hoax. Discourse and Communication, 15(3), 281–307. https://doi.org/10.1177/1750481321989838

Jha, C. K., & Kodila-Tedika, O. (2020). Does social media promote democracy? Some empirical evidence. Journal of Policy Modeling, 42(2), 271–290. https://doi.org/10.1016/j.jpolmod.2019.05.010

Jones-Jang, S. M., Hart, P. S., Feldman, L., & Moon, W. K. (2020). Diversifying or Reinforcing Science Communication? Examining the Flow of Frame Contagion Across Media Platforms. Journalism and Mass Communication Quarterly, 97(1), 98–117. https://doi.org/10.1177/1077699019874731

Kalpokas, I. (2016). Influence Operations : Challenging the Social Media – Democracy Nexus. SAIS Europe Journal of Global Affairs.

Kant, R., & Varea, R. (2021). Spreading (Dis)trust in fiji? exploring covid-19 misinformation on facebook forums. Pacific Journalism Review, 27(1–2), 63–84. https://doi.org/10.24135/pjr.v27i1and2.1166

Latupeirissa, J. E., Pasalbessy, J. D., Leasa, E. Z., & Tuhumury, C. (2021). Penyebaran Berita Bohong (HOAX) Pada Masa Pandemi Covid-19 dan Upaya Penanggulangannya di Provinsi Maluku. Jurnal Belo, 6(2), 179–194. https://doi.org/10.30598/belovol6issue2page179-194

Lawelai, H., & Sadat, A. (2022). Trend Analysis of Positive Sentiment for Special Autonomy for Papua on Twitter. Jurnal Bina Praja, 14(2), 213–224. https://doi.org/10.21787/jbp.14.2022.213-224

Lawelai, H., Sadat, A., & Suherman, A. (2022). DEMOCRACY AND FREEDOM OF OPINION IN SOCIAL MEDIA: SENTIMENT ANALYSIS ON TWITTER. PRAJA: Jurnal Ilmiah Pemerintahan, 10(1), 40–48.

Lawelai, H., Sadat, A., Suherman, A., Agustiyara, A., & Nurmandi, A. (2022). Trend Analysis of Public Enthusiasm for COVID-19 Vaccines on Social Media. Studies in Media and Communication, 10(2), 105. https://doi.org/10.11114/smc.v10i2.5603

Mackay, H. (2017). Social media analytics: Implications for journalism and democracy. Journal of Information Ethics, 26(1), 34–48.

Memon, S. A., & Carley, K. M. (2020). Characterizing covid-19 misinformation communities using a novel twitter dataset. ArXiv Preprint ArXiv:2008.00791.

Nurizar, A. (2020). Digital Television Regulation and its Impact on Indonesia towards Society 5.0. Komunikator, 12(2), 106–115. https://doi.org/10.18196/jkm.122039

Perdana, K. E. (2019). Understanding Distortion of Islam Nusantara on Public Opinion in Indonesia on Political Ambience of 2019 Presidential Election. The International Journal of Pegon : Islam Nusantara Civilization, 2(01), 171–181. https://doi.org/10.51925/inc.v2i01.16

Qadri, M. (2020). Pengaruh Media Sosial Dalam Membangun Opini Publik. Qaumiyyah: Jurnal Hukum Tata Negara, 1(1), 49–63. https://doi.org/10.24239/qaumiyyah.v1i1.4

Rehioui, H., & Idrissi, A. (2020). New clustering algorithms for twitter sentiment analysis. IEEE Systems Journal, 14(1), 530–537. https://doi.org/10.1109/JSYST.2019.2912759

Sadat, A., Lawelai, H., & Suherman, A. (2022). SENTIMENT ANALYSIS ON SOCIAL MEDIA: HATE SPEECH TO THE GOVERNMENT ON TWITTER. PRAJA: Jurnal Ilmiah Pemerintahan, 10(1), 69–76.

Sailunaz, K., & Alhajj, R. (2019). Emotion and sentiment analysis from Twitter text. Journal of Computational Science, 36. https://doi.org/10.1016/j.jocs.2019.05.009

Sari, R. F., Ilmananda, A. S., & Romano, D. M. (2021). Social trust-based blockchain-enabled social media news verification system. Journal of Universal Computer Science, 27(9), 979–998. https://doi.org/10.3897/JUCS.68692

Sawitri, M. Y., & Wiratmaja, I. N. (2021). On the brink of post-democracy: Indonesia’s identity politics in the post-truth era. Politicka Misao, 58(2), 141–159. https://doi.org/10.20901/PM.58.2.06

Sokowati, M. E. (2019). Questioning Public Participation in Social Media Activities in Indonesia. Komunikator, 11(2). https://doi.org/10.18196/jkm.112025

Susanto, E. H. (2019). Social media, hoax, and threats against diversity in Indonesia. International Journal of Innovation, Creativity and Change, 8(12), 328–344.

Tambunan, S. M., Nataliani, Y., & Lestari, E. S. (2021). Perbandingan Klasifikasi dengan Pendekatan Pembelajaran Mesin untuk Mengidentifikasi Tweet Hoaks di Media Sosial Twitter. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 7(2), 112. https://doi.org/10.26418/jp.v7i2.47232

Tan, M., Straughan, P. T., & Cheong, G. (2022). Information trust and COVID-19 vaccine hesitancy amongst middle-aged and older adults in Singapore: A latent class analysis Approach. Social Science and Medicine, 296. https://doi.org/10.1016/j.socscimed.2022.114767

Verma, P. K., Agrawal, P., Madaan, V., & Gupta, C. (2022). UCred: fusion of machine learning and deep learning methods for user credibility on social media. Social Network Analysis and Mining, 12(1). https://doi.org/10.1007/s13278-022-00880-1

Vizoso, Á., & Vázquez-Herrero, J. (2019). Fact-checking platforms in Spanish. Features, organisation and method. Communication and Society, 32(1), 127–142. https://doi.org/10.15581/003.32.1.127-142

Vu, H. T., McCombs, M., Russell, A., & Pain, P. (2020). Deepening the concept of ‘compelling arguments.’ The Agenda Setting Journal, 4(2), 219–240. https://doi.org/10.1075/asj.19009.vu

Wang, L., Wang, Y., de Melo, G., & Weikum, G. (2019). Understanding archetypes of fake news via fine-grained classification. Social Network Analysis and Mining, 9(1). https://doi.org/10.1007/s13278-019-0580-z

Wang, Y., Shi, M., & Zhang, J. (2021). What public health campaigns can learn from people’s Twitter reactions on mask-wearing and COVID-19 Vaccines: a topic modeling approach. Cogent Social Sciences, 7(1). https://doi.org/10.1080/23311886.2021.1959728

Widyastuti, D. A. R. (2021). Using New Media and Social Media in Disaster Communication. Komunikator, 13(2), 100–111. https://doi.org/10.18196/jkm.12074

Yang, K.-C., Pierri, F., Hui, P.-M., Axelrod, D., Torres-Lugo, C., Bryden, J., & Menczer, F. (2021). The COVID-19 infodemic: twitter versus facebook. Big Data & Society, 8(1), 20539517211013860.

Yang, K.-C., Torres-Lugo, C., & Menczer, F. (2020). Prevalence of low-credibility information on twitter during the covid-19 outbreak. ArXiv Preprint ArXiv:2004.14484.

Yue, Z., & Ju, Z. (2021). Legal Dilemma of Fake News Management after ‘Marketplace of Ideas.’ Komunikator, 13(2), 160–174. https://doi.org/10.18196/jkm.12782




DOI: https://doi.org/10.31315/jik.v22i1.8421

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Jurnal Ilmu Komunikasi



 Jurnal Ilmu Komunikasi indexed by:

   

Copyright of Jurnal Ilmu Komunikasi ISSN 1693-3028 (print), ISSN 2407-8220 (online)

Alamat:

Kampus II UPN "Veteran" Yogyakarta, Jl. Babarsari 2, Tambakbayan, Yogyakarta 55281
Phone: (0274)485268

Fax: (0274)487147

Email: jik@upnyk.ac.id 

Web Analytics View My Stats

slot gacor slot