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| Title: | 檢視印尼ChatGPT採用、風險和信任議題之網路討論、 具影響力者及情緒：大數據分析觀點
Examining online discussions, influential actors, and sentiments of ChatGPT adoption, risk and trust in Indonesia: A big data analytics perspective |
| Authors: | 李勇俊
Putra, Rio Oktora Nanda |
| Contributors: | 林翠絹
Lin, Trisha Tsui-Chuan
李勇俊
Putra, Rio Oktora Nanda |
| Keywords: | ChatGPT
X.com
印尼
ChatGPT
Indonesia
adoption
risk
trust
X.com
Diffusion of Innovation theory (DoI)
Latent Dirichlet Allocation (LDA)
topic modeling
influential actors
Social Network Analysis (SNA)
sentiment analysis |
| Date: | 2024 |
| Issue Date: | 2024-06-03 11:53:37 (UTC+8) |
| Abstract: | 印度尼西亞擁有超過2億活躍的互聯網用戶，對ChatGPT來說是一個重要的市場。然而，在2023年初，由於其未註冊的狀態引起了有關監管的潛在禁令的討論。儘管學術界批評存在問題，如抄襲和网络安全风险，但對ChatGPT的興趣仍在增加。過去的研究強調了它的生產效益，但也提出了隱私和网络安全問題，尤其是在教育方面。值得注意的是，在印度尼西亞，有限的研究探討了社交媒體用戶如何討論ChatGPT的採用、風險和信任問題。本研究以創新擴散理論為指導，旨在揭示在線討論中有關ChatGPT的關鍵話題和情緒，以及確定塑造這些討論的有影響力的行為者。
本研究調查了印度尼西亞情境下的ChatGPT採用、風險和信任，重點關注X.com用戶之間的討論。它識別了在線討論中相關的話題和情緒。此外，它還檢查了由有影響力的行為者推動的討論。通過分析從ChatGPT推出到2024年1月31日的推文，本研究採用了使用Python的大數據分析方法。此方法包括時間序列和詞頻分析、潛在狄利克雷分配（LDA）主題建模、情感分析和社交網絡分析（SNA）。
從2022年11月30日到2024年1月31日，有9371條推文討論了ChatGPT的採用，1637條推文討論了ChatGPT的風險，以及950條推文涉及了ChatGPT的信任問題在X.com上。趨勢分析顯示了採用、風險和信任討論中的一致模式，顯著事件推動了興趣的波動。數據顯示2023年1月和2月的活動增加，從2023年6月到8月下降，並從2023年9月開始重新引起興趣，達到2023年12月的高峰。詞頻分析突出顯示了像"chatgpt"和"artificial intelligence"這樣的主要詞彙，而像"afraid"、"danger"和"threat"這樣的詞彙則表明了對風險的關注。此外，“trust”和“human”等反复提到的词语反映了对可靠性和道德影响的讨论，而像“work”、“write”和“search”这样的词语则暗示了在工作场所和内容生成中探索ChatGPT的作用。
LDA主題显示了对ChatGPT响应的探索和实验成为ChatGPT采用相关讨论中最相关的话题，大多数表达了积极的情绪。然而，在风险相关的讨论中，积极和负面情绪之间的极化是明显的，用户表达了对ChatGPT实际好处的赞赏，例如简化任务和提高生产力，但仍然对潜在的缺点持谨慎态度，包括工作岗位替换和对分析思维的影响。同样，与信任相关的讨论主要表现出积极的情绪，反映了用户对ChatGPT能力的信心，尽管对其响应中的不准确性和错误信息持续关注。
社交网络分析揭示了Twitter机器人（如@collegemenfess和@worksfess）等有影响力的行为者，它们在教育和专业背景中与用户进行互动。这些机器人作为匿名讨论的平台，引发了交互并塑造了有关ChatGPT采用的对话。此外，@collegemenfess在ChatGPT与风险相关的讨论中也具有影响力。令人惊讶的是，这些机器人已经积累了可观的关注度，表明它们在引导各自领域内的讨论中具有影响力。此外，像@ainunnajib和@gibran_tweet这样的个人用户在与信任相关的讨论中也成为有影响力的行为者，为有关ChatGPT可靠性和道德影响的讨论做出了贡献。进一步的研究发现，像@tanyakanrl、@tanyarlfes和@ismailfahmi这样的用户在网络内部建立联系并促进了关于ChatGPT的讨论。这些有影响力的行为者的存在突显了像“menfess”
Indonesia, with over 200 million active internet users, is a significant market for ChatGPT. However, in early 2023, concerns about its unregistered status led to discussions about potential bans for oversight. Despite criticisms from academics citing issues like plagiarism and cybersecurity risks, interest in ChatGPT has grown. Past studies highlighted its productivity benefits but also raised concerns about privacy and cybersecurity, especially in education. Notably, there's limited research on how social media users discuss ChatGPT adoption, risks, and trust, particularly in Indonesia. This study, guided by the diffusion of innovation theory, aims to uncover key topics and sentiments in online discussions about ChatGPT, as well as identify influential actors shaping these discussions.
This study investigates the ChatGPT adoption, risk, and trust within the Indonesian context, focusing on discussions among X.com users. It identifies relevant topics and sentiments in online discussions. Additionally, it examines discussions driven by the influential actors. By analyzing tweets spanning from the launch of ChatGPT until January 31, 2024, the study employs a big data analytics approach using Python. This approach includes time series and word frequency analysis, Latent Dirichlet Allocation (LDA) topic modeling, sentiment analysis, and social network analysis (SNA).
Between November 30, 2022, and January 31, 2024, there were 9,371 tweets discussing ChatGPT adoption, 1,637 tweets about ChatGPT risk, and 950 tweets regarding ChatGPT trust on X.com. Trend analysis shows consistent patterns in adoption, risk, and trust discussions, with notable events driving interest fluctuations. The data reveal increased activity in January and February 2023, a dip from June to August 2023, and renewed interest from September 2023 onwards, peaking in December 2023. Word frequency analysis highlights dominant terms like "chatgpt" and "artificial intelligence," with terms like "afraid," "danger," and "threat" indicating concerns about risks. Additionally, recurrent mentions of "trust" and "human" reflect discussions on reliability and ethical implications, while terms like "work," "write," and "search" suggest exploration of ChatGPT's role in the workplace and content generation.
The LDA topic shows the exploration and experimentation with ChatGPT responses emerge as the most relevant topic discussed within the ChatGPT adoption related discussions, with positive sentiment mostly expressed. However, polarization between positive and negative sentiment is evident, particularly in risk-related discussions, where surprising positivity is found alongside anticipated concerns. Users express appreciation for ChatGPT's practical benefits, such as streamlining tasks and enhancing productivity, yet remain cautious about potential drawbacks, including job displacement and impacts on analytical thinking. Similarly, trust-related discussions predominantly exhibit positive sentiments, reflecting users' confidence in ChatGPT's capabilities despite persistent concerns about inaccuracies and misinformation within its responses.
The social network analysis reveals Twitter bots such as @collegemenfess and @worksfess as influential actors, which engage users within the educational and professional contexts. These bots serve as platforms for anonymous discussions, triggering interactions and shaping conversations about ChatGPT adoption. Additionally, @collegemenfess is also influential in ChatGPT risk-related discussions. Surprisingly, these bots have amassed significant followings, indicating their influence in steering discussions within their domains. Additionally, individual users like @ainunnajib and @gibran_tweet emerge as influential actors in trust-related discussions, contributing to the discussions about ChatGPT's reliability and ethical implications. Further examination uncovers users like @tanyakanrl, @tanyarlfes and @ismailfahmi, bridging connections within the network and facilitating discussions about ChatGPT across various user groups. The presence of these influential actors highlights the importance of platforms like ‘menfess’ accounts in fostering open dialogue while preserving user anonymity. |
| Reference: | Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., Farhan, S. S., Khatib, S. E., Rahal, M., Sahban, A., Abdelaziz, D. H., Mansour, N. O., AlZayer, R., Khalil, R., Fekih-Romdhane, F., Hallit, R., … Sallam, M. (2023). Factors influencing attitudes of university students towards ChatGPT and its usage: A multi-national study validating the TAME-ChatGPT survey instrument. Preprints. https://doi.org/10.20944/preprints202309.1541.v1
Abosede, O. E. (2020). Diffusion of innovation theory: An effective approach to accelerate adoption of information and communication technology in twenty-first century knowledge society. International Journal Of Innovative Research & Development, 9(4), 147-155. https://doi.org/10.24940/ijird/2020/v9/i4/APR20061
Adalat, M., Niazi, M. A., & Vasilakos, A. V. (2018). Variations in power of opinion leaders in online communication networks. Royal Society Open Science, 5. https://doi.org/10.1098/rsos.180642
Agrawal, K. P. (2023). Towards adoption of generative ai in organizational settings. Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2023.2240744
AlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). ChatGPT as an educational tool: Opportunities, challenges, and recommendations for communication, business writing, and composition courses. Journal of Artificial Intelligence and Technology, 3(2), 60-68. https://doi.org/10.37965/jait.2023.0184
AlAgha, I. (2021). Topic modeling and sentiment analysis of Twitter discussions on COVID-19 from spatial and temporal perspectives. Journal of Information Science Theory and Practice, 9(1), 35-53. https://doi.org/10.1633/JISTaP.2021.9.1.3
Ali, K., Barhom, N., Marino, F. T., & Duggal, M. (2023). The thrills and chills of ChatGPT: Implications for assessments in undergraduate dental education. Medicine and Pharmacology, Dentistry and Oral Surgery. https://doi.org/10.20944/preprints202302.0513.v1
Al-Razgan, M., Alrowily, A., Al-Matham, R. N., Alghamdi, K. M., Shaabi, M., & Alssum, L. (2021). Using diffusion of innovation theory and sentiment analysis to analyze attitudes toward driving adoption by Saudi women. Technology in Society, 65. https://doi.org/10.1016/j.techsoc.2021.101558
Amaro, I., Barra, P., Greca, A. D., Francese, R., & Tucci, C. (2023). Believe in artificial intelligence? A user study on the ChatGPT’s fake information impact. IEEE Transactions on Computational Social Systems, 1-10. https://doi.org/10.1109/TCSS.2023.3291539
Amijaya, T. F. (2023, March 20). Pemerintah bakal blokir ChatGPT, sebuah langkah maju atau malah sebaliknya? [The government will ban ChatGPT, a step forward or the opposite?]. kumparan. Retrieved December 27, 2023, from https://kumparan.com/tovva-firdansyah/pemerintah-bakal-blokir-chatgpt-sebuah-langkah-maju-atau-malah-sebaliknya-202648AZGmh
Ariansyah, K., Sirait, E. R. E., Nugroho, B. A., & Suryanegara, M. (2021). Drivers of and barriers to e-commerce adoption in Indonesia: Individuals’ perspectives and the implications. Telecommunications Policy, 45(8). https://doi.org/10.1016/j.telpol.2021.102219
Atlas, S. (2023). ChatGPT for higher education and professional development: A guide to conversational AI. Amazon Digital Services LLC - Kdp. https://digitalcommons.uri.edu/cba_facpubs/548/
Ayinde, L., Wibowo, M. P., Ravuri, B., & Emdad, F. B. (2023). ChatGPT as an important tool in organizational management: A review of the literature. Business Information Review, 40(3), 137-149. https://doi.org/10.1177/02663821231187991
Aziza, A.N. (2020). Akun menfess: Pisau bermata dua kebebasan berekspresi di medsos [Menfess account: Double-edged sword of freedom of expression on social media]. Vice. Retrieved May 14, 2024, from https://www.vice.com/id/article/3anavb/sejarah-akun-twitter-menfess-auto-base-di-indonesia-dan-cyberbullying
Baek, T. H., & Kim, M. (2023). Is ChatGPT scary good? How user motivations affect creepiness and trust in generative artificial intelligence. Telematics and Informatics, 83, 102030. https://doi.org/10.1016/j.tele.2023.102030
Baharudin, H. (2023). S’pore and Indonesia to co-develop Bahasa Indonesia ChatGPT-like AI tool. The Straits Times. Retrieved May 14, 2023, from https://www.straitstimes.com/asia/se-asia/s-pore-and-indonesia-to-co-develop-bahasa-indonesia-chatgpt-like-ai-tool
Bang, Y., Cahyawijaya, S., Lee, N., Dai, W., Wilie, B., Lovenia, H., Ji, Z., Tiezheng Yu, T., Chung, W., Do, Q. V., Xu, Y., & Fung, P. (2023). A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity. Computation and Language. https://doi.org/10.48550/arXiv.2302.04023
Basir, A., Puspitasari, E. D., Aristarini, C. C., Sulastri, P. D., & Ausat, A. M. A. (2023). Ethical use of ChatGPT in the context of leadership and strategic decisions. Jurnal Minfo Polgan, 12(1), 1239-1246. https://doi.org/10.33395/jmp.v12i1.12693
Biswas, S. (2023). Role of ChatGPT in computer programming. Mesopotamian Journal of Computer Science, 2023, 8-16. https://doi.org/10.58496/MJCSC/2023/002
Bonsu, E. M., & Baffour-Koduah, D. (2023). From the consumers’ side: Determining students’ perception and intention to use ChatGPT in Ghanaian higher education. Research Square. https://orcid.org/0000-0002-7867-8204
Bukhori, M. F. (2023). The behavioral phenomenon of friend with benefit of alter base @FWBSmg on Twitter. Jurnal Ilmiah Global Education, 4(1), 410–416. https://doi.org/10.55681/jige.v4i1.610
Cambria, E., Das, D., Bandyopadhyay, S., & Feraco, A. (Eds.). (2017). A practical guide to sentiment analysis (Vol. 5). Springer International Publishing. https://doi.org/10.1007/978-3-319-55394-8_1
Caron, C. (2023, March 22). How parents can talk about AI and ChatGPT with their kids. The New York Times. Retrieved November 29, 2023, from https://www.nytimes.com/2023/03/22/well/family/ai-chatgpt-parents-children.html
Carvalho, I., & Ivanov, S. (2023). ChatGPT for tourism: applications, benefits and risks. Tourism Review. https://doi.org/10.1108/TR-02-2023-0088
Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K. (2010). Measuring user influence in Twitter: The million follower fallacy. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 10-17. https://doi.org/10.1609/icwsm.v4i1.14033
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20. https://doi.org/10.1186/s41239-023-00411-8
Chen, J., Kou, G., Wang, H., & Zhao, Y. (2021). Influence identification of opinion leaders in social networks: an agent-based simulation on competing advertisements. Information Fusion, 76, 227-242. https://doi.org/10.1016/j.inffus.2021.06.004
Cheng, M. (2023, December 8). Everything you need to know about Gemini, Google’s new generative AI model. Microsoft Start (MSN). Retrieved May 24, 2024, from https://www.msn.com/en-us/news/technology/everything-you-need-to-know-about-gemini-google-s-new-generative-ai-model/ar-AA1l606P?fullscreen=true
Choudhury, A., & Shamszare, H. (2023). Investigating the impact of user trust on the adoption and use of ChatGPT: Survey analysis. Journal of Medical Internet Research, 25. https://doi.org/10.2196/47184
CNN Indonesia. (2023, May 26). 3 risiko pakai ChatGPT di kampus kata pakar ITB [3 risks of using ChatGPT in campus according to ITB experts]. CNN Indonesia. Retrieved October 26, 2023, from https://www.cnnindonesia.com/teknologi/20230525190343-185-954108/3-risiko-pakai-chatgpt-di-kampus-kata-pakar-itb
Comarela, G., Crovella, M., Almeida, V., & Benevenuto, F. (2012). Understanding factors that affect response rates in twitter. HT '12: Proceedings of the 23rd ACM conference on Hypertext and social media. https://doi.org/10.1145/2309996.2310017
Dacres, S., Haddadi, H., & Purver, M. (2013). Topic and sentiment analysis on OSNs: A case study of advertising strategies on Twitter. Social and Information Networks. https://doi.org/10.48550/arXiv.1312.6635
Damanik, F.J. & Setyohadi, D.B. (2021). Analysis of public sentiment about covid-19 in Indonesia on Twitter using multinomial naive bayes and support vector machine. In IOP Conference Series: Earth and Environmental Science. https://doi.org/10.1088/1755-1315/704/1/012027
Dewi, I. R. (2022, December 6). Viral ChatGPT dan OpenAI, chabot bisa gantikan manusia? [Viral ChatGPT and OpenAI, could chatbots replace humans?]. CNBC Indonesia. Retrieved November 8, 2023, from https://www.cnbcindonesia.com/tech/20221206172849-37-394315/viral-chatgpt-dan-openai-chabot-bisa-gantikan-manusia
Dhokar, A., Hlaoua, L., & Romdhane, L. B. (2021). Tweet contextualization: combining sentence extraction, sentence aggregation and sentence reordering to enhance informativeness and readability. Social Network Analysis and Mining, 11, 16. https://doi.org/10.1007/s13278-021-00724-4
Dwiwina, R.H. & Putri, K.Y.S. (2021). The use of the auto base accounts on Twitter as a media for sharing opinions. Jurnal Ilmu Komunikasi ULTIMACOMM, 13(1). https://doi.org/10.31937/ultimacomm.v13i1.1603
Elias, J. (2023, January 31). Google is asking employees to test potential ChatGPT competitors, including a chatbot called ‘Apprentice Bard’. CNBC. Retrieved May 24, 2024, from https://www.cnbc.com/2023/01/31/google-testing-chatgpt-like-chatbot-apprentice-bard-with-employees.html
Elmezain, M., Othman, E. A., & Ibrahim, H. M. (2021). Temporal degree-degree and closeness-closeness: A new centrality metrics for social network analysis. Mathematics, 9(22). https://doi.org/10.3390/math9222850
Erfina, A., & Nurul, M. R. (2023). Implementation of Naive Bayes classification algorithm for Twitter user sentiment analysis on ChatGPT using Python programming language. Data & Metadata, 2. https://doi.org/10.56294/dm202345
Faiz, A., & Kurniawaty, I. (2023). Tantangan Penggunaan ChatGPT dalam Pendidikan Ditinjau dari Sudut Pandang Moral [Challenges of Using ChatGPT in Education from a Moral Perspective]. Edukatif: Jurnal Ilmu Pendidikan, 5(1). https://doi.org/10.31004/edukatif.v5i1.4779
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International. https://doi.org/10.1080/14703297.2023.2195846
Fauzi, Tuhuteru, L., Sampe, F., Ausat, A. M. A., & Hatta, H. R. (2023). Analysing the role of ChatGPT in improving student productivity in higher education. Journal on Education, 5(4), 14886-14891. https://doi.org/10.31004/joe.v5i4.2563
Fecher, B., Hebing, M., Laufer, M., Pohle, J., & Sofsky, F. (2023). Friend or foe? Exploring the implications of large language models on the science system. AI & Society. https://doi.org/10.1007/s00146-023-01791-1
Finfolk. (2023, June 15). CEO OpenAI, pencipta “ChatGPT” datang ke Indonesia bahas pendidikan dan jawab pertanyaan masyarakat soal perkembangan AI [OpenAI CEO, creator of 'ChatGPT,' comes to Indonesia to discuss education and answer public questions about the development of AI]. Finfolk. Retrieved December 28, 2023, from https://finfolk.co/article/startup/ceo-openai-pencipta-chatgpt-datang-ke-indonesia-bahas-pendidikan-dan-jawab-pertanyaan-masyarakat-soal-perkembangan-ai
Firdaus, S. N., Ding, C., & Sadeghian, A. (2018). Retweet: A popular information diffusion mechanism – A survey paper. Online Social Networks and Media, 6, 26-40. https://doi.org/10.1016/j.osnem.2018.04.001
Fütterer, T., Fischer, C., Alekseeva, A., Chen, X., Tate, T., Warschauer, M., & Gerjets, P. (2023). ChatGPT in education: global reactions to AI innovations. Scientific Reports, 13. https://doi.org/10.1038/s41598-023-42227-6
Gorichanaz, T. (2023). Accused: How students respond to allegations of using ChatGPT on assessments. Learning: Research and Practice, 9(2), 183-196. https://doi.org/10.1080/23735082.2023.2254787
Gude, V. (2023). Factors influencing ChatGPT adoption for product research and information retrieval. Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2023.2280918
Haleem, A., Javaid, M., & Singh, R. P. (2023). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4). https://doi.org/10.1016/j.tbench.2023.100089
Hardiansyah, Z. (2023, February 27). Mengapa ChatGPT Berpotensi Diblokir di Indonesia? [Why is ChatGPT potentially banned in Indonesia?]. Tekno Kompas. https://tekno.kompas.com/read/2023/02/27/16300027/mengapa-chatgpt-berpotensi-diblokir-di-indonesia-
Haryanto, A. T. (2023, February 23). ChatGPT Berpotensi Diblokir di RI, Kecuali... [ChatGPT Potentially Faces Blocking in Indonesia, Unless...]. detikInet. Retrieved December 27, 2023, from https://inet.detik.com/law-and-policy/d-6585709/chatgpt-berpotensi-diblokir-di-ri-kecuali
Helberger, N., & Diakopoulos, N. (2023). ChatGPT and the AI Act. Internet Policy Review, 12(1). https://doi.org/10.14763/2023.1.1682
Hidayatullah, A. F., Apong, R. A., Lai, D. T.C., & Qazi, A. (2023). Corpus creation and language identification for code-mixed Indonesian-Javanese-English tweets. PeerJ Computer Science, 9. https://doi.org/10.7717/peerj-cs.1312
Hosseini, M., Gao, C. A., Liebovitz, D., Carvalho, A., Ahmad, F. S., Luo, Y., MacDonald, N., Holmes, K., & Kho, A. (2023). An exploratory survey about using ChatGPT in education, healthcare, and research. medRxiv. https://doi.org/10.1101/2023.03.31.23287979
Hox, J. J. (2017). Computational social science methodology, anyone? VII European Congress of Methodology, 13(1). https://doi.org/10.1027/1614-2241/a000127
Hu, K. (2023, February 2). ChatGPT sets record for fastest-growing user base - analyst note. Reuters. Retrieved November 29, 2023, from https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/
Hung, J., & Chen, J. (2023). The benefits, risks and regulation of using ChatGPT in Chinese academia: A content analysis. Social Sciences, 12(7), 380. https://doi.org/10.3390/socsci12070380
IDN Times. (2023, March 26). 5 sisi terang dan gelap ChatGPT menurut sejumlah pakar UI [5 pros and cons of ChatGPT according to UI experts]. IDN Times. Retrieved November 8, 2023, from https://www.idntimes.com/news/indonesia/rochmanudin-wijaya/5-sisi-terang-dan-gelap-chatgpt-menurut-sejumlah-pakar-ui?page=all
Irani, D., Webb, S., Pu, C., & Li, K. (2010). Study of trend-stuffing on twitter through text classification. In Collaboration, Electronic messaging, Anti-Abuse and Spam Conference (CEAS). https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1c3be9108479950f8b20400857ab66e2175a7a4f
Ivanov, S., & Soliman, M. (2023). Game of algorithms: ChatGPT implications for the future of tourism education and research. Journal of Tourism Futures, 9(2), 214-221. https://doi.org/10.1108/JTF-02-2023-0038
Jo, H. (2023). Understanding AI tool engagement: A study of ChatGPT usage and word-of-mouth among university students and office workers. Telematics and Informatics, 85. https://doi.org/10.1016/j.tele.2023.102067
Kalla, D., & Smith, N. (2023). Study and analysis of Chat GPT and its impact on different fields of study. International Journal of Innovative Science and Research Technology, 8(3). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4402499
Kamaliah, A. (2023, June 16). Bos ChatGPT minta tolong ke Indonesia, ada apa? [ChatGPT boss seeks help from Indonesia, what's going on?]. detikInet. Retrieved December 6, 2023, from https://inet.detik.com/science/d-6776611/bos-chatgpt-minta-tolong-ke-indonesia-ada-apa
Karo, R.P.P.K. (2022). Hate speech: Penyimpangan terhadap UU ITE, kebebasan berpendapat dan nilai-nilai keadilan bermartabat [Hate speech: Deviation from the ITE Law, freedom of expression, and the values of dignified justice]. Jurnal Lemhanas RI, 10(4). https://doi.org/10.55960/jlri.v10i4.370
Khalil, M., & Er, E. (2023). Will ChatGPT get you caught? Rethinking of plagiarism detection. Artificial Intelligence. https://doi.org/10.48550/arXiv.2302.04335
Khlaif, Z. N., Mousa, A., Hattab, M. K., Itmazi, J., Hassan, A. A., Sanmugam, M., & Ayyoub, A. (2023). The potential and concerns of using AI in scientific research: ChatGPT performance evaluation. JMIR Medical Education, 9. https://doi.org/10.2196/47049
Khurana, M., Gulati, A., & Singh, S. (2018). Sentiment analysis framework of Twitter data using classification. In 2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC). https://doi.org/10.1109/PDGC.2018.8745748
Kiryakova, G., & Angelova, N. (2023). ChatGPT—A challenging tool for the university professors in their teaching practice. Education Sciences, 13(10), 1056. https://doi.org/10.3390/educsci13101056
Korkmaz, A., aktürk, C., & talan, T. (2023). Analyzing the user’s sentiments of ChatGPT using Twitter data. Iraqi Journal For Computer Science and Mathematics, 4(2), 202–214. https://doi.org/10.52866/ijcsm.2023.02.02.018
Kraugusteeliana, Indriana, I. H., Krisnanik, E., Muliawati, A., & Irmanda, H. N. (2023). Utilisation of ChatGPT's artificcial intelligence in improving the quality and productivity of lecturers' work. Jurnal Pendidikan dan Konseling, 5(2). https://doi.org/10.31004/jpdk.v5i2.13650
Kulshrestha, J., Zafar, M., Noboa, L., Gummadi, K., & Ghosh, S. (2015). Characterizing information diets of social media users. Proceedings of the International AAAI Conference on Web and Social Media, 9(1). https://doi.org/10.1609/icwsm.v9i1.14634
Kushwaha, A. K., Kumar, P., & Kar, A. K. (2021). What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial Marketing Management, 98, 207-221. https://doi.org/10.1016/j.indmarman.2021.08.011
Li, L., Ma, Z., Fan, L., Lee, S., Yu, H., & Hemphill, L. (2023). ChatGPT in education: a discourse analysis of worries and concerns on social media. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12256-9
Lian, Y., Tang, H., Xiang, M., & Dong, X. (2024). Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media. Technology in Society, 76. https://doi.org/10.1016/j.techsoc.2023.102442
Loria, S. (2020, April 26). textblob Documentation. TextBlob. Retrieved April 9, 2024, from https://textblob.readthedocs.io/en/dev/quickstart.html#sentiment-analysis
Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73. https://doi.org/10.1080/15252019.2018.1533501
Lyu, Z., & Qiao, L. (2020). Analysis of healthcare big data. Future Generation Computer Systems, 109, 103-110. https://doi.org/10.1016/j.future.2020.03.039
Ma, R., Zhang, Q., Wang, J., Cui, L., & Huang, X. (2018). Mention recommendation for multimodal microblog with cross-attention memory network. SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. https://doi.org/10.1145/3209978.3210026
Machmudi, M. I. A. (2023, March 25). Kehadiran ChatGPT disebut akan ciptakan siswa yang tak jujur [The presence of ChatGPT is said to create dishonest students]. Media Indonesia. Retrieved August 26, 2023, from https://mediaindonesia.com/humaniora/568470/kehadiran-chatgpt-disebut-akan-ciptakan-siswa-yang-tak-jujur
Maharani, D. C. T. (2023, April). Ngeri, peneliti temukan ChatGPT bisa buat malware canggih [Scary, researchers find ChatGPT can create advanced malware]. Liputan 6. Retrieved October 26, 2023, from https://www.liputan6.com/tekno/read/5261742/ngeri-peneliti-temukan-chatgpt-bisa-buat-malware-canggih?page=2
McBee, J. C., Han, D. Y., Liu, L., Ma, L., Adjeroh, D. A., Xu, D., & Hu, G. (2023). Interdisciplinary inquiry via PanelGPT: Application to explore chatbot application in sports rehabilitation. medRxiv. https://doi.org/10.1101/2023.07.23.23292452
Mich, L., & Garigliano, R. (2023). ChatGPT for e-tourism: a technological perspective. Information Technology & Tourism, 25, 1-12. https://doi.org/10.1007/s40558-023-00248-x
Milieu Insight. (February 22, 2023). Leading user concerns held about ChatGPT among respondents in Southeast Asia as of February 2023, by selected country [Graph]. In Statista. Retrieved May 24, 2024, from https://www.statista.com/statistics/1383112/sea-top-user-concerns-about-chat-gpt-by-country/
Misnawati, M. (2023). ChatGPT: keuntungan, risiko, dan penggunaan bijak dalam era kecerdasan buatan [ChatGPT: benefits, risks, and wise use in the age of artificial intelligence]. Prosiding Seminar Nasional Pendidikan, Bahasa, Sastra, Seni, dan Budaya, 2(1), 54-67. https://doi.org/10.55606/mateandrau.v2i1.221
Mnif, E., Lacombe, I., & Jarboui, A. (2021). Users’ perception toward Bitcoin Green with big data analytics. Society and Business Review, 16(4), 592-615. https://doi.org/10.1108/SBR-02-2021-0016
Mutoffar, M. M., Kuswayati, S., Anggraeny, F. T., & Sumarni, T. (2023). Exploring the potential of ChatGPT in improving online marketing and promotion of MSMEs. Jurnal Minfo Polgan, 12(1), 480-489. https://doi.org/10.33395/jmp.v12i2.12440
Naurah, N. (2023, June 22). Daftar platform AI yang paling sering digunakan di Indonesia, ChatGPT teratas [List of AI platforms most frequently used in Indonesia, ChatGPT at the top]. GoodStats. Retrieved August 14, 2023, from https://goodstats.id/article/daftar-platform-ai-yang-paling-sering-digunakan-di-indonesia-chatgpt-teratas-DPyuE
Negara, E. S., & Triadi, D. (2022). Topic modeling using latent dirichlet allocation (LDA) on Twitter data with Indonesia keyword. Bulletin of Social Informatics Theory and Application, 5(2), 124–132. https://doi.org/10.31763/businta.v5i2.455
Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192. https://doi.org/10.1126/science.adh2586
O’Callaghan, D., Greene, D., Carthy, J., & Cunningham, P. (2015). An analysis of the coherence of descriptors in topic modeling. Expert Systems with Applications, 42(13), 5645-5657. https://doi.org/10.1016/j.eswa.2015.02.055
Okey, O. D., Udo, E. U., Rosa, R. L., Rodríguez, D. Z., & Kleinschmidt, J. H. (2023). Investigating ChatGPT and cybersecurity: A perspective on topic modeling and sentiment analysis. Computers & Security, 135. https://doi.org/10.1016/j.cose.2023.103476
O'Neill, A. (2023a, November 9). Indonesia - total population 2018-2028. Statista. Retrieved December 28, 2023, from https://www.statista.com/statistics/294100/total-population-of-indonesia/
O'Neill, A. (2023b, December 21). Indonesia - Statistics & facts. Statista. Retrieved January 4, 2024, from https://www.statista.com/topics/2398/indonesia/#topicOverview
Oruçoğlu, N., & Kılınç, E. A. (2023). Performance of artificial intelligence chatbot as a source of patient information on anti-rheumatic drug use in pregnancy. Journal of Surgery and Medicine, 7(10), 651-655. https://doi.org/10.28982/josam.7977
Oviedo-Trespalacios, O., Peden, A. E., Cole-Hunter, T., Costantini, A., Haghani, M., Rod, J.E., Kelly, S., Torkamaan, H., Tariq, A., Newton, J. D. A., Gallagher, T., Steinert, S., Filtness, A. J., & Reniers, G. (2023). The risks of using ChatGPT to obtain common safety-related information and advice. Safety Science, 167. https://doi.org/10.1016/j.ssci.2023.106244
Pardos, Z. A., & Bhandari, S. (2023). Learning gain differences between ChatGPT and human tutor generated algebra hints. Computers and Society. https://doi.org/10.48550/arXiv.2302.06871
Paul, J., Ueno, A., & Dennis, C. (2023). ChatGPT and consumers: Benefits, Pitfalls and Future Research Agenda. International Journal of Consumer Studies, 47(4), 1213-1225. https://doi.org/10.1111/ijcs.12928
Pavlik, J. V. (2023). Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education. Journalism & Mass Communication Educator, 78(1), 84-93. https://doi.org/10.1177/10776958221149577
Petrosyan, A. (2023, August 30). Number of internet users by country 2023. Statista. Retrieved December 28, 2023, from https://www.statista.com/statistics/262966/number-of-internet-users-in-selected-countries/
Petrovic, S., Osborne, M., & Lavrenko, V. (2021). RT to Win! Predicting Message Propagation in Twitter. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 586-589. https://doi.org/10.1609/icwsm.v5i1.14149
Pipin, S. J., Sinaga, F. M., Winardi, S., & Hakim, M. N. (2023). Sentiment Analysis Classification of ChatGPT on Twitter Big Data in Indonesia Using Fast R-CNN. Jurnal Media Informatika Budidarma, 7(4). http://dx.doi.org/10.30865/mib.v7i4.6816
Politis, I., Georgiadis, G., Kopsacheilis, A., Nikolaidou, A., & Papaioannou, P. (2021). Capturing Twitter negativity pre- vs. mid-COVID-19 pandemic: An LDA application on London public transport system. Sustainability, 13(23). https://doi.org/10.3390/su132313356
Polyzos, E., & Wang, F. (2022). Twitter and market efficiency in energy markets: Evidence using LDA clustered topic extraction. Energy Economics, 114. https://doi.org/10.1016/j.eneco.2022.106264
Populix. (2023, June). Unveiling the tech revolution: How technology reshapes the future of work. https://info.populix.co/product/consumer-trend-report/download?report=2023-06-the-future-of-work
Prasasti, G. D. (2023, March 29). Para pakar UI ungkap sisi terang dan kelam chatgpt bagi dunia pendidikan [UI experts reveal the bright and dark sides of ChatGPT for education]. Liputan 6. Retrieved December 28, 2023, from https://www.liputan6.com/tekno/read/5246450/para-pakar-ui-ungkap-sisi-terang-dan-kelam-chatgpt-bagi-dunia-pendidikan?page=2
Putra, G. A., Taniady, V., & Halmadiningrat, I. M. (2023). Tantangan hukum: Keakuratan informasi layanan AI chatbot dan perlindungan hukum terhadap penggunanya [Legal challenges: Accuracy of information from AI chatbot services and legal protection for its users]. Jurnal Rechts Vinding: Media Pembinaan Hukum Nasional, 12(2). http://dx.doi.org/10.33331/rechtsvinding.v12i2.1258
Qureshi, K. A. (2021). Multi-class and automated tweet categorization. Computation and Language. https://doi.org/10.48550/arXiv.2112.03005
R, S., Mujahid, M., Rustam, F., Shafique, R., Chunduri, V., Villar, M. G., Ballester, J. B., Diez, I. d. l. T., & Ashraf, I. (2023). Analyzing sentiments regarding ChatGPT using Novel BERT: A machine learning approach. Information, 14(9), 474. https://doi.org/10.3390/info14090474
Rahayu, D.A.P., Kuntur, S., & Hayatin, N. (2018). Sarcasm detection on Indonesian Twitter feeds. In 2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI). https://doi.org/10.1109/EECSI.2018.8752913
Rahmawati, F. N. (2023, June 16). CEO OpenAI ke Indonesia, jelaskan peran ChatGPT di pendidikan [OpenAI CEO in Indonesia, explaining the role of ChatGPT in education]. Sampaijauh.com. Retrieved December 6, 2023, from https://sampaijauh.com/ceo-openai-ke-indonesia-jelaskan-peran-chatgpt-di-pendidikan-37151
Ramadhan, R., & Fikrie, M. (2022, December 5). Apa itu ChatGPT, kecerdasan buatan OpenAI yang viral? [What is ChatGPT, the OpenAI artificial intelligence that went viral?]. Kumparan Tech. Retrieved October 27, 2023, from https://kumparan.com/kumparantech/apa-itu-chatgpt-kecerdasan-buatan-openai-yang-viral-1zNcVcTO7sz/full
Raman, R., Mandal, S., Das, P., Kaur, T., JP, S., & Nedungadi, P. (2023). University students as early adopters of ChatGPT: Innovation diffusion study. Research Square. https://doi.org/10.21203/rs.3.rs-2734142/v1
Rao, A., Pang, M., Kim, J., Kamineni, M., Lie, W., Prasad, A. K., Landman, A., Dreyer, K. J., & Succi, M. D. (2023). Assessing the utility of ChatGPT throughout the entire clinical workflow. medRxiv. https://doi.org/10.1101/2023.02.21.23285886
Rehman, A. U., Jiang, A., Rehman, A., Paul, A., din, S., & Sadiq, M. T. (2023). Identification and role of opinion leaders in information diffusion for online discussion network. Journal of Ambient Intelligence and Humanized Computing, 15301–15313. https://doi.org/10.1007/s12652-019-01623-5
Řehůřek, R., & Sojka, P. (2010, May 22). Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, 45--50. https://is.muni.cz/publication/884893/en
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York : Free Press.
Roose, K. (2022, December 5). The brilliance and weirdness of ChatGPT. The New York Times. Retrieved November 29, 2023, from https://www.nytimes.com/2022/12/05/technology/chatgpt-ai-twitter.html
Rosa, N. (2023, May 17). Dosen ITB Ingatkan Untuk Tidak Terlalu Percaya ChatGPT, Apa Alasannya? [ ITB Lecturer Reminds Not to Trust ChatGPT Too Much, Why?]. Detik Edu. Retrieved November 8, 2023, from https://www.detik.com/edu/detikpedia/d-6724724/dosen-itb-ingatkan-untuk-tidak-terlalu-percaya-chatgpt-apa-alasannya
Rosenblatt, K. (2022, December 2). An AI chatbot went viral. Some say it's better than Google; others worry it's problematic. NBC News. Retrieved November 27, 2023, from https://www.nbcnews.com/tech/tech-news/chatgpt-ai-chatbot-viral-rcna59628
Salah, M., Alhalbusi, H., Ismail, M. M., & Abdelfattah, F. (2023). Chatting with ChatGPT: Decoding the Mind of Chatbot Users and Unveiling the Intricate Connections between User Perception, Trust and Stereotype Perception on Self-Esteem and Psychological Well-being. Research Square. https://doi.org/10.21203/rs.3.rs-2610655/v2
Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887
Sallam, M., Salim, N., Barakat, M., Al-Mahzoum, K., Al-Tammemi, A. B., Malaeb, D., Hallit, R., & Hallit, S. (2023a). Assessing attitudes and usage of ChatGPT in Jordan among health students: A validation study of the technology acceptance model-based scale (TAME-ChatGPT). JMIR Medical Education. https://doi.org/10.2196/48254
Sallam, M., Salim, N. A., Barakat, M., Al-Mahzoum, K., Al-Tammemi, A. B., Malaeb, D., Hallit, R., & Hallit, S. (2023b). Assessing health students' attitudes and usage of ChatGPT in Jordan: Validation study. JMIR Medical Education, 9. https://doi.org/10.2196/48254
Sallam, M., Salim, N. A., Barakat, M., & Al-Tammemi, A. B. (2023c). ChatGPT applications in medical, dental, pharmacy, and public health education: A descriptive study highlighting the advantages and limitations. Narra J, 3(1). https://doi.org/10.52225/narra.v3i1.103
Samanta, O. (2023, July 17). ChatGPT users, revenue & statistics 2023. Priori Data. Retrieved November 27, 2023, from https://prioridata.com/data/chatgpt-users/
Sánchez-Fernández, R., & Jiménez-Castillo, D. (2021). How social media influencers affect behavioural intentions towards recommended brands: the role of emotional attachment and information value. Journal of Marketing Management, 37(11-12), 1123-1147. https://doi.org/10.1080/0267257X.2020.1866648
Santika, M. A. A. (2023, May 11). Tantangan ChatGPT dalam Bahasa Indonesia [Challenges of ChatGPT in Indonesian]. GLAIR.ai. Retrieved August 17, 2023, from https://glair.ai/blog-posts-id/tantangan-chatgpt-dalam-bahasa-indonesia
Savitri, D. (2023, March 15). Soal ChatGPT, dosen hukum UGM: Sebaiknya dilarang di universitas [Regarding ChatGPT, law professor at UGM: It is advised to be prohibited in universities.]. detikcom. Retrieved December 28, 2023, from https://www.detik.com/edu/perguruan-tinggi/d-6620083/soal-chatgpt-dosen-hukum-ugm-sebaiknya-dilarang-di-universitas
Shahsavar, Y., & Choudhury, A. (2023). User intentions to use ChatGPT for self-diagnosis and health-related purposes: Cross-sectional survey study. JMIR Human Factors. https://doi.org/10.2196/47564
Shanmugam, J. K., Ping, T. A., & Thuraisamy, R. (2019). The effect of perceived characteristics of DOI and technology adoption on SMEs performance in Malaysia. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 4773-4779. http://www.doi.org/10.35940/ijrte.D7292.118419
Singh, J., & Gupta, V. (2016). Text stemming: Approaches, applications, and challenges. ACM Computing Surveys, 49(3), 1–46. https://doi.org/10.1145/2975608
Sivarajah, U., Irani, Z., Gupta, S., & Mahroof, K. (2020). Role of big data and social media analytics for business to business sustainability: A participatory web context. Industrial Marketing Management, 86, 163-179. https://doi.org/10.1016/j.indmarman.2019.04.005
Statista. (2023, September 13). Countries with most X/Twitter users 2023. Statista. Retrieved November 10, 2023, from https://www.statista.com/statistics/242606/number-of-active-twitter-users-in-selected-countries/
Sundar, S. S., & Liao, M. (2023). Calling BS on ChatGPT: Reflections on AI as a communication source. Journalism & Communication Monographs, 25(2), 165-180. https://doi.org/10.1177/15226379231167135
Syahrial, M. (2022). Sering dipakai di Twitter, apa arti kata menfess? [Often used on Twitter, what does the word 'menfess' mean?]. Retrieved May 14, 2024, from https://www.kompas.com/wiken/read/2022/05/15/202458881/sering-dipakai-di-twitter-apa-arti-kata-menfess
Talan, T., & Kalinkara, Y. (2023). The role of artificial intelligence in higher education: ChatGPT assessment for anatomy course. International Journal of Management Information Systems, 7(1), 33-40. https://doi.org/10.33461/uybisbbd.1244777
Tang, L., Ni, Z., Xiong, H., & Zhu, H. (2015). Locating targets through mention in Twitter. World Wide Web, 18, 1019–1049. https://doi.org/10.1007/s11280-014-0299-8
Tang, X., Zhang, C., Meng, W., & Wang, K. (2020). Joint user mention behavior modeling for mentionee recommendation. Applied Intelligence, 50, 2449–2464. https://doi.org/10.1007/s10489-020-01635-1
The Indonesian Ministry of Law and Human Rights. (2023). Dirjen imigrasi terbitkan golden visa pertama untuk pendiri ChatGPT, Samuel Altman [Director general of immigration issues first golden visa for ChatGPT founder, Samuel Altman]. Kantor Imigrasi Kelas I Non TPI Jakarta Pusat. Retrieved from https://kanimjakpus.kemenkumham.go.id/en/berita-utama/470-dirjen-imigrasi-terbitkan-golden-visa-pertama-untuk-pendiri-chatgpt-samuel-altman
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10. https://doi.org/10.1186/s40561-023-00237-x
Tounsi, A., Elkefi, S., & Bhar, S. L. (2023). Exploring the reactions of early users of ChatGPT to the tool using Twitter data: Sentiment and topic analyses. 2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET). https://doi.org/10.1109/IC_ASET58101.2023.10150870
Tubishat, M., Al-Obeidat, F., & Shuhaiber, A. (2023). Sentiment analysis of using ChatGPT in education. 2023 International Conference on Smart Applications, Communications and Networking (SmartNets). https://doi.org/10.1109/SmartNets58706.2023.10215977
Umeugo, W., Pandya, S. Y., & Lowrey, K. (2023). Factors affecting the adoption of secure software practices in small and medium enterprises that build software in-house. International Journal of Advanced Research in Computer Science, 14(2). http://dx.doi.org/10.26483/ijarcs.v14i2.6955
Walter, S., & Brüggemann, M. (2020). Opportunity makes opinion leaders: analyzing the role of first-hand information in opinion leadership in social media networks. Information, Communication & Society, 23(2), 267-287. https://doi.org/10.1080/1369118X.2018.1500622
Wang, S., Ren, D., & Lyu, X. (2023). Core issues and key arguments of ChatGPT: Topic mining and sentiment analysis based on U.S. news reports. Image and Graphics, 176–185. https://doi.org/10.1007/978-3-031-46314-3_14
Wang, Y. F., Lee, S. K., & Ye, Q. (2021). Opinion leaders in eco-innovation diffusion: Analysis of information networks for waste separation in Shanghai. Resources, Conservation and Recycling, 174. https://doi.org/10.1016/j.resconrec.2021.105822
Wang, Z., Liu, H., Liu, W., & Wang, S. (2020). Understanding the power of opinion leaders’ influence on the diffusion process of popular mobile games: Travel Frog on Sina Weibo. Computers in Human Behavior, 109. https://doi.org/10.1016/j.chb.2020.106354
Wei, Y., Guo, L., Lian, C., & Chen, J. (2023). ChatGPT: Opportunities, risks and priorities for psychiatry. Asian Journal of Psychiatry, 90. https://doi.org/10.1016/j.ajp.2023.103808
Wu, X., Duan, R., & Ni, J. (2023). Unveiling security, privacy, and ethical concerns of ChatGPT. Journal of Information and Intelligence. https://doi.org/10.1016/j.jiixd.2023.10.007
X.com a. (n.d.). User access tokens (3-legged OAuth flow). Twitter Developer. Retrieved January 1, 2024, from https://developer.twitter.com/en/docs/authentication/oauth-1-0a/obtaining-user-access-tokens
X.com b. (n.d.). Data dictionary: Standard v1.1. Twitter Developer Platform. Retrieved April 9, 2024, from https://developer.twitter.com/en/docs/twitter-api/v1/data-dictionary/object-model/user
X.com c. (n.d.). About Automated account labels. Twitter Help Center. Retrieved April 18, 2024, from https://help.twitter.com/en/using-x/automated-account-labels
Xue, J., Chen, J., Chen, C., Zheng, C., Li, S., & Zhu, T. (2020). Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter. PLOS ONE, 15(9). https://doi.org/10.1371/journal.pone.0239441
Yan, Y., Toriumi, F., & Sugawara, T. (2021). Understanding how retweets influence the behaviors of social networking service users via agent-based simulation. Computational Social Networks, 8. https://doi.org/10.1186/s40649-021-00099-8
Yuan, L., Li, G., Chen, J., & Li, Y. (2023). The effect of opinion emotion on information dissemination in social networks. Procedia Computer Science, 221, 216-226. https://doi.org/10.1016/j.procs.2023.07.030
Yunitasari, Y., Musdholifah, A., & Sari, A.K. (2019). Sarcasm detection for sentiment analysis in Indonesian tweets. Indonesian Journal of Computing and Cybernetics Systems (IJCCS), 13(1). https://doi.org/10.22146/ijccs.41136
Zhang, J., Tang, J., Li, J., Liu, Y., & Xing, C. (2015). Who influenced you? Predicting retweet via social influence locality. ACM Transactions on Knowledge Discovery from Data, 9(3), 1–26. https://doi.org/10.1145/2700398
Zhou, S., Kan, P., Huang, Q., & Silbernagel, J. (2023). A guided latent Dirichlet allocation approach to investigate real-time latent topics of Twitter data during Hurricane Laura. Journal of Information Science, 49(2), 465-479. https://doi.org/10.1177/01655515211007724
Zou, W., Li, J., Yang, Y., & Tang, L. (2023). Exploring the early adoption of Open AI among laypeople and technical professionals: An analysis of Twitter conversations on #ChatGPT and #GPT3. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2023.2295725 |
| Description: | 碩士
國立政治大學
國際傳播英語碩士學位學程(IMICS)
110461001 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110461001 |
| Data Type: | thesis |
| Appears in Collections: | [國際傳播英語碩士學程] 學位論文
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| 100101.pdf | | 6494Kb | Adobe PDF | 0 | View/Open |
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