SOCIAL CONTROL OF MAINSTREAM MEDIA THROUGH TWITTER ACCOUNTS: SENTIMENT ANALYSIS AND SOCIAL NETWORK ON ROAD DAMAGE CASES
Abstract
Abstract
A video criticizing the damaged road conditions in Lampung has gone viral after being uploaded on social media. This infrastructure case has become a trending topic on the Twitter platform since April 2023. Not only in Lampung, people in other areas have also expressed their disappointment through various citizen protests. This problem prompted President Jokowi to directly review the condition of the damaged roads in Lampung and decide quickly to resolve the problem. The damaged road became a hot topic of conversation on Twitter. This research was conducted to analyze the sentiments of Twitter users towards opinions related to damaged roads and to analyze the social networks that are formed to find out the actors who play a role in spreading information. Research using descriptive and quantitative methods The process of crawling data on Twitter uses Netlytic.org and then analyzing the system level, as well as text analysis, through the keyword extractor and manual categories at Netlytic.org. The results of the study show that the main actors in the #jalanrusak communication network on Twitter are mainstream media accounts. This shows the position of the mainstream media as channeling aspirations and protecting people's rights, as well as its function as a tool of government control. Although some mainstream media also use it to spread political issues. Considering that 2023 is a political year ahead of the 2024 elections, This moment is considered strategic to attack the government and the ruling party. On the other hand, the president's quick response is seen as part of his self-image, which also has an impact on the image of the presidential candidate in his party. The sentiments of Twitter users in the discussion of #jalanrusak are more negative.
References
Aditama, M. I., Pratama, R. I., Wiwaha, K. H. & Rakhmawati, N. A., 2020. Analisis Klasifikasi Sentimen Pengguna Media Sosial Twitter Terhadap Pengadaan Vaksin COVID-19. Journal Information Engineering and Educational Technology ISSN, 4(2), pp. 90-92.
Bratawisnu, M. K. & Alamsyah, A., 2018. Social Network Analysis untuk Analisa Interaksi User di Media Sosial Mengenai Bisnis E-Commerce (Studi Kasus: Lazada, Tokopedia dan Elevania). Almana: Jurnal Manajemen dan Bisnis , 2(2), pp. 107-115.
Cahyono, Y., 2017. Analisis Sentiment Media Twitter Menggunakan Naive Bayes Classifier dengan Feature Selection Particle Swarm Optimization dan Term frequency. METODE, 2(1), pp. 14-19.
Dewi Kumalasari, R. A., Pradana, M. & Miftahuddin, A., 2022. Diskusi Metaverse di Twitter (#Metaverse): Analisis Jejaring Sosial. Jurnal Ideas, 8(3), pp. 841-852.
Fatanti, M. N., 2014. Twitter dan masa Depan Politik Indonesia: Analisis Perkembangan Komunikasi Politik Lokal melalui Internet. Jurnal IPTEK-KOM, 16(1), pp. 17-28.
Ghassani, V. I. & Sukowati, P., 2016. Bentuk Hubungan Pers dengan Pemerintah Terkait dengan Fungsi Media sebagai Kontrol Sosial. Publisia, 1(2), pp. 170-182.
Hadiana, A. I. & Witanti, W., 2017. Analisis Jejaring Sosial Menggunakan Social Network Analysis untuk Membantu Social CRM bagi UMKM di Cimahi. Bandung, UNIKOM, pp. 29-36.
Hartanto, 2017. Text Mining dan Sentimen Analisis Twitter pada Gerakan LGBT. Intuisi: Jurnal Psikologi Ilmiah, 9(1), pp. 18-25.
Inayah, D. & Purba, F. L., 2020. Implementation Social Network Analysis in Distribution of Corona Virus (Covid-19) Information on Twitter. Seminar Nasional Official Statistic, Volume 1, pp. 292-299.
Jastania, Z. et al., 2022. Analyzing Public Discussions about #SaudiWomenCanDrive Using Network Science. IEEE Access, Volume 10, pp. 4739-4749.
Kusasi, F. & Iranita, I., 2019. Analisis Jaringan Sosial Bursa Jual Beli Facebook di Kepulauan Riau. Bahtera Inovasi, 3(1), pp. 67-81.
Mishra, N. & Singh, A., 2018. Use of twitter data for waste minimisation in beef supply chain. Annals of Operations Research, 270(1-2), pp. 337-359.
Mudjianto, B. & Dunan, A., 2020. Media Mainstream jadi Rujukan Media Sosial. Jakarta: Kementerian Kominfo.
Nursiyono, J. A. & Chotimah, C., 2021. Analisis Sentimen Netizen Twitter terhadap Pemberitaan PPN Sembako dan Jasa Pendidikan dengan Pendekatan Social Network Analysis dan naive Bayes Classifier. J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika, 14(1), pp. 52-58.
Rathore, A. K., Kar, A. K. & Ilavarasan, P. V., 2017. Social media analytics: Literature review and directions for future research. Decision Analysis, 14(4), pp. 229-249.
Salim, S. S. & Mayary, J., 2020. Analisis Sentimen Pengguna Twitter terhadap Dompet Elektronik dengan Metode Lexicon Based dan K-Nearest Neighbor. Jurnal Ilmiah Informatika Komputer, 25(1), pp. 1-17.
Scott, J., 2017. Social Network Analysis (4th ed.). SAGE Publications.
Sugiyono, 2011. Metode Penelitian Kualitatif, Kuantitatif dan R&D. Bandung: Alfabeta.
Suryono, S., Utami, E. & Luthfi, E. T., 2018. Klasifikasi Sentimen pada Twitter dengan Naive Bayes Classifier. Angkasa J. Ilm. Bid. Teknol, 10(1), pp. 89-96.
Syarief, F., 2017. Pemanfaatan Media Sosial dalam Proses Pembentukan Opini Publik (Analisa Wacana Twitter SBY). Jurnal Komunikasi, 8(3), pp. 262-266.
Wahyu, Y. M. W., Berto, A. R. & Murwani, E., 2022. Analisis Sentimen Jaringan Pesan Kolom Komentar Video Wonderful Indonesia 2022 Jagad Jawi yang Dipengaruhi Budaya. Avant Garde J. Ilmu Komun, 10(2), pp. 201-2016.
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