SCRATCH as Social Network: Topic Modeling and Sentiment Analysis in SCRATCH Projects

被引:0
作者
Grassl, Isabella [1 ]
Fraser, Gordon [1 ]
机构
[1] Univ Passau, Passau, Germany
来源
2022 ACM/IEEE 44TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING-SOFTWARE ENGINEERING IN SOCIETY, ICSE-SEIS 2022 | 2022年
关键词
Scratch; topic modeling; sentiment analysis; social network; HATE SPEECH; TALKING;
D O I
暂无
中图分类号
学科分类号
摘要
Societal matters like the Black Lives Matter (BLM) movement influence software engineering, as the recent debate on replacing certain discriminatory terms such as whitelist/blacklist has shown. Identifying relevant and trending societal matters is important, and often done for traditional social media channels such as Twitter. In this paper we explore whether this type of analysis can also be used for introspection of the software world, by looking at the thriving scene of SCRATCH programmers. The educational programming language SCRATCH is not only used for teaching programming concepts, but also offers a platform for young programmers to express and share their creativity on any topics of relevance. By automatically analyzing titles and project comments in a dataset of 106.032 SCRATCH projects, we explore which topics are common in the SCRATCH community, whether socially relevant events are reflected, and how the sentiment in the comments discussing these topics is. It turns out that the diversity of topics within the SCRATCH projects makes the analysis process challenging. Our results nevertheless show that topics from pop and net culture are present, and even recent societal events such as the Covid-19 pandemic or BLM are to some extent reflected in SCRATCH. The tone in the comments is mostly positive with catchy youth language. Hence, despite the challenges, SCRATCH projects can be studied in the same way as social networks, which opens up new possibilities to improve our understanding of the behavior and motivation of novice programmers.
引用
收藏
页码:143 / 148
页数:6
相关论文
共 50 条
  • [41] Jointly Modeling Community and Topic in Social Network
    Zhang, Yunlei
    Ning, Nianwen
    Lv, Jinna
    Song, Chenguang
    Wu, Bin
    KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, KSEM 2019, PT I, 2019, 11775 : 209 - 221
  • [42] Topic modeling and Sentiment Analysis-based Recommender system: A literature review
    Ben Nsir, Doniazed
    Ben Brahim, Afef
    Masri, Hela
    2022 8TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT'22), 2022, : 903 - 907
  • [43] When Sentiment Analysis Meets Social Network: A Holistic User Behavior Modeling in Opinionated Data
    Gong, Lin
    Wang, Hongning
    KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2018, : 1455 - 1464
  • [44] Investigating ChatGPT and cybersecurity: A perspective on topic modeling and sentiment analysis
    Okey, Ogobuchi Daniel
    Udo, Ekikere Umoren
    Rosa, Renata Lopes
    Rodriguez, Demostenes Zegarra
    Kleinschmidt, Joao Henrique
    COMPUTERS & SECURITY, 2023, 135
  • [45] Public Opinion About COVID-19 on a Microblog Platform in China: Topic Modeling and Multidimensional Sentiment Analysis of Social Media
    Guo, Feipeng
    Liu, Zixiang
    Lu, Qibei
    Ji, Shaobo
    Zhang, Chen
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2024, 26
  • [46] Exploring the Chinese Public's Perception of Omicron Variants on Social Media: LDA-Based Topic Modeling and Sentiment Analysis
    Wang, Han
    Sun, Kun
    Wang, Yuwei
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (14)
  • [47] Public Opinions on ChatGPT : An Analysis of Reddit Discussions by Using Sentiment Analysis, Topic Modeling, and SWOT Analysis
    Naing, Shwe Zin Su
    Udomwong, Piyachat
    DATA INTELLIGENCE, 2024, 6 (02) : 344 - 374
  • [48] Transportation sentiment analysis using word embedding and ontology-based topic modeling
    Ali, Farman
    Kwak, Daehan
    Khan, Pervez
    El-Sappagh, Shaker
    Ali, Amjad
    Ullah, Sana
    Kim, Kye Hyun
    Kwak, Kyung-Sup
    KNOWLEDGE-BASED SYSTEMS, 2019, 174 : 27 - 42
  • [49] Fashion informatics of the Big 4 Fashion Weeks using topic modeling and sentiment analysis
    Yeong-Hyeon Choi
    Seungjoo Yoon
    Bin Xuan
    Sang-Yong Tom Lee
    Kyu-Hye Lee
    Fashion and Textiles, 8
  • [50] Fashion informatics of the Big 4 Fashion Weeks using topic modeling and sentiment analysis
    Choi, Yeong-Hyeon
    Yoon, Seungjoo
    Xuan, Bin
    Lee, Sang-Yong Tom
    Lee, Kyu-Hye
    FASHION AND TEXTILES, 2021, 8 (01)