Analisis Sentimen Data Twitter terkait ChatGPT menggunakan Orange Data Mining
DOI:
https://doi.org/10.25126/jtiik.20241127276Abstrak
Perkembangan teknologi bergerak begitu cepat, diikuti dengan popularitas media sosial yang semakin meluas. Platform media sosial mampu membangun profil big-data pengguna, dengan melacak setiap aktivitas seperti partisipasi, pengiriman pesan, dan kunjungan situs Web. Saat ini banyak orang sering membagikan kritik terhadap sesuatu melalui platform media sosial seperti Facebook, Twitter, Instagram, dan lainnya. Sehingga perlu diketahui bagaimana komentar dari pengguna media sosial yang menghasilkan reaksi masyarakat terhadap chatGPT yang dirilis oleh OpenAI. Banyaknya komentar di Twitter menyebabkan sulitnya mengetahui kecenderungan respon masyarakat. Tujuan dari penelitian ini yaitu melakukan analisis sentimen postingan publik di Twitter untuk memberikan wawasan tentang sikap dan persepsi orang tentang suatu peristiwa. Penelitian ini memberikan ilustrasi peran Twitter dalam menampung postingan pengguna Twitter terkait chatGPT. Hasil penelitian ini dapat digunakan oleh pemangku kepentingan untuk menentukan kebijakan dalam penggunaan chatGPT. Penelitian ini menganalisis sebanyak 5.192 postingan tweet bahasa Inggris dan 641 tweet bahasa Indonesia, mulai dari tanggal 27 April hingga 8 Mei 2023. Tanggapan positif, negatif, dan netral diolah menggunakan perangkat lunak Orange Data Mining dengan algoritma Ekman untuk menganalisis emosi data tweet yang diperoleh. Hasil menunjukan bahwa chatGPT mendapatkan tanggapan netral berbahasa Inggris dengan nilai sebesar 54,72%, tanggapan positif sebesar 31,64%, dan tanggapan negatif sebesar 13,64%. Hasil analisis sentimen berbahasa Indonesia tidak jauh berbeda, dengan nilai tanggapan netral sebesar 63,96%, tanggapan positif 23,56%, dan tanggapan negatif 12,48%. Sehingga dapat disimpulkan bahwa, rilisnya chatGPT mayoritas publik memberikan tanggapan netral atau tidak terdapat penolakan.
Abstract
Technological developments move so fast, followed by the increasingly widespread popularity of social media. Social media platforms can build big-data profiles of users by tracking every activity such as participation, messaging, and website visits. Currently, many people often share criticism of something through social media platforms, such as Facebook, Twitter, Instagram, and others. So it is necessary to know how comments from social media users generate public reactions to chatGPT released by OpenAI. A lot of comments on Twitter make it difficult to know the trend of people's responses. The purpose of this research is to conduct sentiment analysis of public posts on Twitter to provide insights into people's attitudes and perceptions regarding a particular event. This research illustrates Twitter's role in accommodating Twitter user posts regarding chatGPT. The results of this study can be used by stakeholders in making policies on the use of chatGPT. This study analyzed 5,192 posts in English and 641 tweets in Indonesian from April 27 to May 8, 2023. The positive, negative, and neutral responses are processed using Orange Data Mining software with the Ekman algorithm to analyze the emotional content of the acquired tweet data. The results show that chatGPT received neutral responses in English with a value of 54.72%, positive responses of 31.64%, and negative responses of 13.64%. The results of sentiment analysis in Indonesian were not much different, with neutral responses of 63.96%, positive responses of 23.56%, and negative responses of 12.48%. So it can be concluded that after the release of chatGPT, the majority of the public gave neutral responses or no rejection.
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