社群媒體上的生成式人工智慧輿情探勘

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陳敬元(Ching-Yuan Chen) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

社群媒體上的生成式人工智慧輿情探勘
(Public Opinion Mining of Generative AI)

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至系統瀏覽論文 (2029-7-8以後開放)

摘要(中)

生成式人工智慧 (GAI) 是當前發展最快且廣受討論的技術之一，對社會產生了重大影響。生成式AI能夠產生大量豐富且有趣的內容，但也因為一些問題而受到批評，例如侵犯版權或智慧財產權。本研究旨在利用自然語言處理技術探討社群媒體用戶對生成式AI內容的看法和情緒反應。研究聚焦於社群媒體平台Reddit，深入收集和分析用戶的討論和意見。數據範圍涵蓋2023年7月至2024年4月，來自多個子板塊和關鍵字，涵蓋文字、圖片和影片生成等各種生成式AI技術。本研究使用RoBERTa預訓練模型進行兩階段情感分類，分析貼文和評論中表達的情緒，並將其分類為主動和被動情緒。研究還使用潛在狄利克雷分佈來識別主要的討論主題，探討用戶對不同類型生成式AI技術的主要關注點。研究結果表明，只有相對較低比例的用戶對生成式AI技術表達了負面情緒，這表明即使GAI引發了許多爭議，大多數公眾仍對其保持積極的態度。雖然使用者對各種類型生成式AI技術的主要關注點略有不同，也存在許多相似的討論話題。本研究為技術開發者、政策制定者和社群媒體平台管理者提供了了解公眾情緒和解決生成式AI相關問題的看法。

摘要(英)

Generative artificial intelligence (GAI) is one of the fastest developing and widely discussed technologies, having a significant impact on society. However, while generative AI can produce a lot of rich and interesting content, it has also been criticized for some issues such as violating copyright or intellectual property rights. This study aims to explore social media users′ views and emotional responses to generative AI content using natural language processing techniques. The research focuses on Reddit, a social media platform, by deeply collecting and analyzing user discussions and opinions. The data spans multiple subreddits and keywords from July 2023 to April 2024, covering various generative AI technologies such as text, image, and video generation. This study employs the RoBERTa pre-trained model for a two-stage sentiment classification to analyze the emotions expressed in posts and comments, categorizing them into active and passive sentiments. Additionally, the study uses Latent Dirichlet Allocation to identify the main discussion topics, exploring users′ primary concerns regarding different types of generative AI technologies. The study′s findings indicate that a relatively low proportion of users expressed negative sentiments toward generative AI technology. This suggests that despite the numerous controversies surrounding GAI, the majority of the public maintains a positive outlook on it, and although there are slight differences in the main concerns regarding various types of generative AI technologies, there are also many similar discussion topics. This research provides insights for technology developers, policymakers, and social media platform managers to understand public sentiments and address concerns related to generative AI.

關鍵字(中)

★ 生成式人工智慧
★ 社群媒體
★ 輿情分析
★ 情感分析
★ 隱含狄利克雷分布
★ 情感分類

關鍵字(英)

★ Generative AI
★ Social media
★ Opinion mining
★ Sentiment analysis
★ LDA
★ Emotion Classification

論文目次

摘要 i
Abstract ii
Table of Contents iii
List of Figures v
List of Tables vi
I. Introduction 1
1-1 Research Background 1
1-2 Research Motivation 4
1-3 Research Objectives 8
II. Related Work 9
2-1 Public perceptions of emerging technology 9
2-2 Generative AI 11
2-3 Opinion mining and Sentiment analysis 14
III. Experiment Design 19
3-1 Research Framework 19
3-2 Data collection 19
3-3 Dataset 25
3-3-1 Data Characteristics 25
3-3-2 Data Preprocessing 27
3-3-3 Data Cleaning 28
3-4 Pretrained Model 30
3-5 Training Dataset 31
3-6 Sentiment Analysis 32
3-7 Topic Modeling 33
3-8 Emotion Classification 36
IV. Result and Discussion 42
4-1 Descriptive Statistical Analysis Result 42
4-2 Trend Analysis 47
4-3 Topic Modeling Result 49
4-3-1 Text Generative AI 49
4-3-2 Image Generative AI 50
4-3-3 Video Generative AI 51
4-3-4 Audio Generative AI 52
4-3-5 Comprehensive discussion of Generative AI 53
4-4 Emotion classification 54
V. Conclusion and Contribution 61
5-1 Conclusion 61
5-2 Contribution 63
5-3 Limitations and Future Research 66
References 67

參考文獻

References
Adoma, Acheampong Francisca, Nunoo-Mensah Henry, and Wenyu Chen. 2020.
“Comparative Analyses of Bert, Roberta, Distilbert, and Xlnet for Text-Based
Emotion Recognition.” Pp. 117–21 in 2020 17th International Computer
Conference on Wavelet Active Media Technology and Information Processing
(ICCWAMTIP).
Aydin, M. Aslı. 2021. “Using Generative Adversarial Networks for Handling Class
Imbalance Problem.” Pp. 1–4 in 2021 29th Signal Processing and
Communications Applications Conference (SIU).
Bian Jiang, Yoshigoe Kenji, Hicks Amanda, Yuan Jiawei, He Zhe, Xie Mengjun, Guo
Yi, Prosperi Mattia, Salloum Ramzi, and Modave François. 2016. “Mining
Twitter to Assess the Public Perception of the ‘Internet of Things.’” PLOS
ONE 11(7):e0158450. doi: 10.1371/journal.pone.0158450.
Butler, Tom. 2020. “What’s Next in the Digital Transformation of Financial
Industry?” IT Professional 22(01):29–33. doi: 10.1109/MITP.2019.2963490.
Center Pew Research. 2022. “1. How Americans think about artificial intelligence.”
Pew Research Center: Internet, Science & Tech. Retrieved February 29, 2024
(https://www.pewresearch.org/internet/2022/03/17/how-americans-think
about-artificial-intelligence/).
Chakravorti, Bhaskar, Ajay Bhalla, and Ravi Shankar Chaturvedi. 2019. “Which
Countries Are Leading the Data Economy.” Harvard Business Review 1:2–8.
Chiarello, Filippo, Vito Giordano, Irene Spada, Simone Barandoni, and Gualtiero
Fantoni. 2024. “Future Applications of Generative Large Language Models: A
Data-Driven Case Study on ChatGPT.” Technovation 133:103002. doi:
10.1016/j.technovation.2024.103002.
Chiu, Thomas K. F. 2023. “The Impact of Generative AI (GenAI) on Practices,
Policies and Research Direction in Education: A Case of ChatGPT and
Midjourney.” Interactive Learning Environments 0(0):1–17. doi:
10.1080/10494820.2023.2253861.
Cortis, Keith, and Brian Davis. 2021. “Over a Decade of Social Opinion Mining: A
67
Systematic Review.” Artificial Intelligence Review 54(7):4873–4965. doi:
10.1007/s10462-021-10030-2.
Dai, Junqi, Hang Yan, Tianxiang Sun, Pengfei Liu, and Xipeng Qiu. 2021. “Does
Syntax Matter? A Strong Baseline for Aspect-Based Sentiment Analysis with
RoBERTa.”
Delrow, Collin. 2023. “The Week in Generative AI: November 17, 2023 Edition.”
Quad. Retrieved May 18, 2024 (https://www.quad.com/insights/the-week-in
generative-ai-november-17-2023-edition).
Demszky, Dorottya, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav
Nemade, and Sujith Ravi. 2020. “GoEmotions: A Dataset of Fine-Grained
Emotions.”
Ding, Yuxin, and Shengli Yan. 2015. “Topic Optimization Method Based on
Pointwise Mutual Information.” Pp. 148–55 in Neural Information Processing,
edited by S. Arik, T. Huang, W. K. Lai, and Q. Liu. Cham: Springer
International Publishing.
Došilović, Filip Karlo, Mario Brčić, and Nikica Hlupić. 2018. “Explainable Artificial
Intelligence: A Survey.” Pp. 0210–15 in 2018 41st International Convention
on Information and Communication Technology, Electronics and
Microelectronics (MIPRO).
Ekman, Paul. 1992. “An Argument for Basic Emotions.” Cognition & Emotion. doi:
10.1080/02699939208411068.
Golda, Abenezer, Kidus Mekonen, Amit Pandey, Anushka Singh, Vikas Hassija,
Vinay Chamola, and Biplab Sikdar. 2024. “Privacy and Security Concerns in
Generative AI: A Comprehensive Survey.” IEEE Access 12:48126–44. doi:
10.1109/ACCESS.2024.3381611.
Gupta, Maanak, CharanKumar Akiri, Kshitiz Aryal, Eli Parker, and Lopamudra
Praharaj. 2023. “From ChatGPT to ThreatGPT: Impact of Generative AI in
Cybersecurity and Privacy.”
Haque, Mubin Ul, Isuru Dharmadasa, Zarrin Tasnim Sworna, Roshan Namal
Rajapakse, and Hussain Ahmad. 2022. “‘I Think This Is the Most Disruptive
Technology’: Exploring Sentiments of ChatGPT Early Adopters Using Twitter
Data.”
68
He, Tianxiang. 2019. “The Sentimental Fools and the Fictitious Authors: Rethinking
the Copyright Issues of AI-Generated Contents in China.” Asia Pacific Law
Review 27(2):218–38. doi: 10.1080/10192557.2019.1703520.
Hou, Qixuan, Meng Han, and Zhipeng Cai. 2020. “Survey on Data Analysis in Social
Media: A Practical Application Aspect.” Big Data Mining and Analytics
3(4):259–79. doi: 10.26599/BDMA.2020.9020006.
Imran, Muhammad, Saman Hina, and Mirza Mahmood Baig. 2022. “Analysis of
Learner’s Sentiments to Evaluate Sustainability of Online Education System
during COVID-19 Pandemic.” Sustainability 14(8):4529. doi:
10.3390/su14084529.
Jain, Mayank, and Prasanna Kulkarni. 2022. “Application of AI, IOT and ML for
Business Transformation of The Automotive Sector.” Pp. 1270–75 in 2022
International Conference on Decision Aid Sciences and Applications (DASA).
Japkowicz, Nathalie, and Shaju Stephen. 2002. “The Class Imbalance Problem: A
Systematic Study.” Intelligent Data Analysis 6(5):429–49. doi: 10.3233/IDA
2002-6504.
Jelodar, Hamed, Yongli Wang, Chi Yuan, Xia Feng, Xiahui Jiang, Yanchao Li, and
Liang Zhao. 2019. “Latent Dirichlet Allocation (LDA) and Topic Modeling:
Models, Applications, a Survey.” Multimedia Tools and Applications
78(11):15169–211. doi: 10.1007/s11042-018-6894-4.
Jing, Yongcheng, Yezhou Yang, Zunlei Feng, Jingwen Ye, Yizhou Yu, and Mingli
Song. 2020. “Neural Style Transfer: A Review.” IEEE Transactions on
Visualization and Computer Graphics 26(11):3365–85. doi:
10.1109/TVCG.2019.2921336.
Kelley, Patrick Gage, Yongwei Yang, Courtney Heldreth, Christopher Moessner,
Aaron Sedley, Andreas Kramm, David T. Newman, and Allison Woodruff.
2021. “Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial
Intelligence in 8 Countries.” Pp. 627–37 in Proceedings of the 2021
AAAI/ACM Conference on AI, Ethics, and Society, AIES ’21. New York, NY,
USA: Association for Computing Machinery.
Khan, Salman, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad
Shahbaz Khan, and Mubarak Shah. 2022. “Transformers in Vision: A Survey.”
69
ACM Computing Surveys 54(10s):200:1-200:41. doi: 10.1145/3505244.
Kim, Dong Sung, and Jong Woo Kim. 2014. “Public Opinion Mining on Social
Media: A Case Study of Twitter Opinion on Nuclear Power.” Pp. 224–28 in.
Kim, Song-Kyoo Amang, and Un-Hong Wong. 2023. “ChatGPT Impacts on
Academia.” Pp. 422–26 in 2023 International Conference on System Science
and Engineering (ICSSE).
Kingma, Diederik P., and Max Welling. 2022. “Auto-Encoding Variational Bayes.”
Kostygina, Ganna, Yoonsang Kim, Zachary Seeskin, Felicia LeClere, and Sherry
Emery. 2023. “Disclosure Standards for Social Media and Generative
Artificial Intelligence Research: Toward Transparency and Replicability.”
Social Media + Society 9(4):20563051231216947. doi:
10.1177/20563051231216947.
Leiter, Christoph, Ran Zhang, Yanran Chen, Jonas Belouadi, Daniil Larionov, Vivian
Fresen, and Steffen Eger. 2023. “ChatGPT: A Meta-Analysis after 2.5
Months.”
Liu, Bing. 2010. “Sentiment Analysis and Subjectivity.”
Liu, Bing, and Lei Zhang. 2012. “A Survey of Opinion Mining and Sentiment
Analysis.” Pp. 415–63 in Mining Text Data, edited by C. C. Aggarwal and C.
Zhai. Boston, MA: Springer US.
Liu, Yinhan, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer
Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019.
“RoBERTa: A Robustly Optimized BERT Pretraining Approach.”
Lo, Chung Kwan. 2023. “What Is the Impact of ChatGPT on Education? A Rapid
Review of the Literature.” Education Sciences 13(4):410. doi:
10.3390/educsci13040410.
Luque, Amalia, Alejandro Carrasco, Alejandro Martín, and Ana de las Heras. 2019.
“The Impact of Class Imbalance in Classification Performance Metrics Based
on the Binary Confusion Matrix.” Pattern Recognition 91:216–31. doi:
10.1016/j.patcog.2019.02.023.
McIntosh, Timothy R., Teo Susnjak, Tong Liu, Paul Watters, and Malka N.
70
Halgamuge. 2023. “From Google Gemini to OpenAI Q* (Q-Star): A Survey of
Reshaping the Generative Artificial Intelligence (AI) Research Landscape.”
Md Suhaimin, Mohd Suhairi, Mohd Hanafi Ahmad Hijazi, Ervin Gubin Moung,
Puteri Nor Ellyza Nohuddin, Stephanie Chua, and Frans Coenen. 2023.
“Social Media Sentiment Analysis and Opinion Mining in Public Security:
Taxonomy, Trend Analysis, Issues and Future Directions.” Journal of King
Saud University - Computer and Information Sciences 35(9):101776. doi:
10.1016/j.jksuci.2023.101776.
Medhat, Walaa, Ahmed Hassan, and Hoda Korashy. 2014. “Sentiment Analysis
Algorithms and Applications: A Survey.” Ain Shams Engineering Journal
5(4):1093–1113.
Mehta, Ivan. 2023. “Everything Announced at OpenAI’s First Developer Event.”
TechCrunch. Retrieved May 18, 2024
(https://techcrunch.com/2023/11/06/everything-announced-at-openais-first
developer-event/).
Messaoudi, Chaima, Zahia Guessoum, and Lotfi Ben Romdhane. 2022. “Opinion
Mining in Online Social Media: A Survey.” Social Network Analysis and
Mining 12(1):25. doi: 10.1007/s13278-021-00855-8.
Miyazaki, Kunihiro, Taichi Murayama, Takayuki Uchiba, Jisun An, and Haewoon
Kwak. 2024. “Public Perception of Generative AI on Twitter: An Empirical
Study Based on Occupation and Usage.” EPJ Data Science 13(1):2. doi:
10.1140/epjds/s13688-023-00445-y.
Novobilská, Linda. 2023. “Free and Open Source Software Licensing Requirements
and Copyright Infringement Involving Artificial Intelligence Technologies.”
masterThesis, Humboldt-Universität zu Berlin.
Oh, SeungJun, and Dong-Keun Kim. 2022. “Comparative Analysis of Emotion
Classification Based on Facial Expression and Physiological Signals Using
Deep Learning.” Applied Sciences 12(3):1286. doi: 10.3390/app12031286.
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya,
Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman,
Shyamal Anadkat, Red Avila, Igor Babuschkin, Suchir Balaji, Valerie Balcom,
Paul Baltescu, Haiming Bao, Mohammad Bavarian, Jeff Belgum, Irwan Bello,
71
Jake Berdine, Gabriel Bernadett-Shapiro, Christopher Berner, Lenny
Bogdonoff, Oleg Boiko, Madelaine Boyd, Anna-Luisa Brakman, Greg
Brockman, Tim Brooks, Miles Brundage, Kevin Button, Trevor Cai, Rosie
Campbell, Andrew Cann, Brittany Carey, Chelsea Carlson, Rory Carmichael,
Brooke Chan, Che Chang, Fotis Chantzis, Derek Chen, Sully Chen, Ruby
Chen, Jason Chen, Mark Chen, Ben Chess, Chester Cho, Casey Chu, Hyung
Won Chung, Dave Cummings, Jeremiah Currier, Yunxing Dai, Cory
Decareaux, Thomas Degry, Noah Deutsch, Damien Deville, Arka Dhar, David
Dohan, Steve Dowling, Sheila Dunning, Adrien Ecoffet, Atty Eleti, Tyna
Eloundou, David Farhi, Liam Fedus, Niko Felix, Simón Posada Fishman,
Juston Forte, Isabella Fulford, Leo Gao, Elie Georges, Christian Gibson, Vik
Goel, Tarun Gogineni, Gabriel Goh, Rapha Gontijo-Lopes, Jonathan Gordon,
Morgan Grafstein, Scott Gray, Ryan Greene, Joshua Gross, Shixiang Shane
Gu, Yufei Guo, Chris Hallacy, Jesse Han, Jeff Harris, Yuchen He, Mike
Heaton, Johannes Heidecke, Chris Hesse, Alan Hickey, Wade Hickey, Peter
Hoeschele, Brandon Houghton, Kenny Hsu, Shengli Hu, Xin Hu, Joost
Huizinga, Shantanu Jain, Shawn Jain, Joanne Jang, Angela Jiang, Roger Jiang,
Haozhun Jin, Denny Jin, Shino Jomoto, Billie Jonn, Heewoo Jun, Tomer
Kaftan, Łukasz Kaiser, Ali Kamali, Ingmar Kanitscheider, Nitish Shirish
Keskar, Tabarak Khan, Logan Kilpatrick, Jong Wook Kim, Christina Kim,
Yongjik Kim, Jan Hendrik Kirchner, Jamie Kiros, Matt Knight, Daniel
Kokotajlo, Łukasz Kondraciuk, Andrew Kondrich, Aris Konstantinidis, Kyle
Kosic, Gretchen Krueger, Vishal Kuo, Michael Lampe, Ikai Lan, Teddy Lee,
Jan Leike, Jade Leung, Daniel Levy, Chak Ming Li, Rachel Lim, Molly Lin,
Stephanie Lin, Mateusz Litwin, Theresa Lopez, Ryan Lowe, Patricia Lue,
Anna Makanju, Kim Malfacini, Sam Manning, Todor Markov, Yaniv
Markovski, Bianca Martin, Katie Mayer, Andrew Mayne, Bob McGrew, Scott
Mayer McKinney, Christine McLeavey, Paul McMillan, Jake McNeil, David
Medina, Aalok Mehta, Jacob Menick, Luke Metz, Andrey Mishchenko,
Pamela Mishkin, Vinnie Monaco, Evan Morikawa, Daniel Mossing, Tong Mu,
Mira Murati, Oleg Murk, David Mély, Ashvin Nair, Reiichiro Nakano, Rajeev
Nayak, Arvind Neelakantan, Richard Ngo, Hyeonwoo Noh, Long Ouyang,
Cullen O’Keefe, Jakub Pachocki, Alex Paino, Joe Palermo, Ashley Pantuliano,
Giambattista Parascandolo, Joel Parish, Emy Parparita, Alex Passos, Mikhail
Pavlov, Andrew Peng, Adam Perelman, Filipe de Avila Belbute Peres, Michael
Petrov, Henrique Ponde de Oliveira Pinto, Michael, Pokorny, Michelle
Pokrass, Vitchyr H. Pong, Tolly Powell, Alethea Power, Boris Power,
Elizabeth Proehl, Raul Puri, Alec Radford, Jack Rae, Aditya Ramesh,
72
Cameron Raymond, Francis Real, Kendra Rimbach, Carl Ross, Bob Rotsted,
Henri Roussez, Nick Ryder, Mario Saltarelli, Ted Sanders, Shibani Santurkar,
Girish Sastry, Heather Schmidt, David Schnurr, John Schulman, Daniel
Selsam, Kyla Sheppard, Toki Sherbakov, Jessica Shieh, Sarah Shoker, Pranav
Shyam, Szymon Sidor, Eric Sigler, Maddie Simens, Jordan Sitkin, Katarina
Slama, Ian Sohl, Benjamin Sokolowsky, Yang Song, Natalie Staudacher,
Felipe Petroski Such, Natalie Summers, Ilya Sutskever, Jie Tang, Nikolas
Tezak, Madeleine B. Thompson, Phil Tillet, Amin Tootoonchian, Elizabeth
Tseng, Preston Tuggle, Nick Turley, Jerry Tworek, Juan Felipe Cerón Uribe,
Andrea Vallone, Arun Vijayvergiya, Chelsea Voss, Carroll Wainwright, Justin
Jay Wang, Alvin Wang, Ben Wang, Jonathan Ward, Jason Wei, C. J.
Weinmann, Akila Welihinda, Peter Welinder, Jiayi Weng, Lilian Weng, Matt
Wiethoff, Dave Willner, Clemens Winter, Samuel Wolrich, Hannah Wong,
Lauren Workman, Sherwin Wu, Jeff Wu, Michael Wu, Kai Xiao, Tao Xu,
Sarah Yoo, Kevin Yu, Qiming Yuan, Wojciech Zaremba, Rowan Zellers,
Chong Zhang, Marvin Zhang, Shengjia Zhao, Tianhao Zheng, Juntang
Zhuang, William Zhuk, and Barret Zoph. 2024. “GPT-4 Technical Report.”
Ortutay, Barbara, and Matt O’brien. n.d. “ChatGPT-Maker OpenAI Hosts Its First Big
Tech Showcase as the AI Startup Faces Growing Competition.” Retrieved
May 18, 2024 (https://techxplore.com/news/2023-11-chatgpt-maker-openai
hosts-big-tech.html).
Pan, Xingzhou, and Yu Xue. 2023. “Advancements of Artificial Intelligence
Techniques in the Realm About Library and Information Subject—A Case
Survey of Latent Dirichlet Allocation Method.” IEEE Access 11:132627–40.
doi: 10.1109/ACCESS.2023.3334619.
Pavlik, John 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. doi:
10.1177/10776958221149577.
Pearce, Hammond, Baleegh Ahmad, Benjamin Tan, Brendan Dolan-Gavitt, and
Ramesh Karri. 2022. “Asleep at the Keyboard? Assessing the Security of
GitHub Copilot’s Code Contributions.” Pp. 754–68 in 2022 IEEE Symposium
on Security and Privacy (SP).
PENG, Ling, Geng CUI, Mengzhou ZHUANG, and Chunyu LI. 2014. “What Do
73
Seller Manipulations of Online Product Reviews Mean to Consumers?” Hong
Kong Institute of Business Studies Working Paper Series.
Picazo-Sanchez, Pablo, and Lara Ortiz-Martin. 2024. “Analysing the Impact of
ChatGPT in Research.” Applied Intelligence 54(5):4172–88. doi:
10.1007/s10489-024-05298-0.
Qian, Cheng, Nitya Mathur, Nor Hidayati Zakaria, Rameshwar Arora, Vedika Gupta,
and Mazlan Ali. 2022. “Understanding Public Opinions on Social Media for
Financial Sentiment Analysis Using AI-Based Techniques.” Information
Processing & Management 59(6):103098. doi: 10.1016/j.ipm.2022.103098.
Rita, Paulo, Nuno António, and Ana Patrícia Afonso. 2023. “Social Media Discourse
and Voting Decisions Influence: Sentiment Analysis in Tweets during an
Electoral Period.” Social Network Analysis and Mining 13(1):46. doi:
10.1007/s13278-023-01048-1.
Rushdi Saleh, M., M. T. Martín-Valdivia, A. Montejo-Ráez, and L. A. Ureña-López.
2011. “Experiments with SVM to Classify Opinions in Different Domains.”
Expert Systems with Applications 38(12):14799–804. doi:
10.1016/j.eswa.2011.05.070.
Samuelson, Pamela. 2023. “Generative AI Meets Copyright.” Science 381(6654):158
61. doi: 10.1126/science.adi0656.
Vaswani, Ashish, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N.
Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. “Attention Is All You
Need.” Advances in Neural Information Processing Systems 30.
Wankhade, Mayur, Annavarapu Chandra Sekhara Rao, and Chaitanya Kulkarni. 2022.
“A Survey on Sentiment Analysis Methods, Applications, and Challenges.”
Artificial Intelligence Review 55(7):5731–80. doi: 10.1007/s10462-022
10144-1.
Wessel, Michael, Martin Adam, Alexander Benlian, and Ferdinand Thies. 2023.
“Generative AI and Its Transformative Value for Digital Platforms.” Journal of
Management Information Systems.
Wu, Tianyu, Shizhu He, Jingping Liu, Siqi Sun, Kang Liu, Qing-Long Han, and Yang
Tang. 2023. “A Brief Overview of ChatGPT: The History, Status Quo and
Potential Future Development.” IEEE/CAA Journal of Automatica Sinica
74
10(5):1122–36. doi: 10.1109/JAS.2023.123618.
Yu, Wenjin, Yuehua Liu, Tharam Dillon, Wenny Rahayu, and Fahed Mostafa. 2022.
“An Integrated Framework for Health State Monitoring in a Smart Factory
Employing IoT and Big Data Techniques.” IEEE Internet of Things Journal
9(3):2443–54. doi: 10.1109/JIOT.2021.3096637.
Zhang Baobao, and Dafoe Allan. 2019. “Artificial Intelligence: American Attitudes
and Trends.”

指導教授

曾筱珽蔡邦維(Hsiao-Ting,Tseng Pang-Wei Tsai)

審核日期

2024-7-10

推文