Text Mining of Twitter Data for Mapping the Digital Humanities Research Trends: A Case Study

被引:0
|
作者
Sawale, Arti [1 ]
Walia, Paramjeet Kaur [1 ]
机构
[1] Univ Delhi, Dept Lib & Informat Sci, Delhi 110007, India
来源
DESIDOC JOURNAL OF LIBRARY & INFORMATION TECHNOLOGY | 2023年 / 43卷 / 04期
关键词
Digital humanities; DH; Twitter; Big data; Text mining; !text type='Python']Python[!/text; Tweets;
D O I
10.14429/djlit.43.4.19236
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Digital humanities have become a more relevant field of study due to the extraordinary growth in digitisation of the humanities data. Due to collaborative development of humanities and computing, many academics are convinced of the worth of digital humanities (DH) that actually provides the best insight into humanities studies. The panoramic view of the development of big data in humanities reflects its trendy directions and evoked new challenges in DH. It is complicated to analysis the objectives of digital humanities data with simple data analysis tools where as text mining can help to facilitate the qualitative findings in DH. In the humanities disciplines, data is often in the form of unstructured and text mining is a way of structuring and analysing digitised text-as-data. Twitter is a online social networking platform which offers an opportunity for quality information sharing, collaborative participation of digital humanities community. This paper is attempted to study the extensibility of digital humanities on twitter and also to interpret the evolution of twitter usage by analysing tweets posted related to DH via python data analysis.
引用
收藏
页码:258 / 265
页数:8
相关论文
共 50 条
  • [1] Exploring the digital humanities research agenda: a text mining approach
    Joo, Soohyung
    Hootman, Jennifer
    Katsurai, Marie
    JOURNAL OF DOCUMENTATION, 2022, 78 (04) : 853 - 870
  • [2] A social network analysis of Twitter: Mapping the digital humanities community
    Grandjean, Martin
    COGENT ARTS & HUMANITIES, 2016, 3
  • [3] Exploring research trends in big data across disciplines: A text mining analysis
    Mohammadi, Ehsan
    Karami, Amir
    JOURNAL OF INFORMATION SCIENCE, 2022, 48 (01) : 44 - 56
  • [4] Using Text Mining Techniques to Identify Research Trends: A Case Study of Design Research
    Nie, Binling
    Sun, Shouqian
    APPLIED SCIENCES-BASEL, 2017, 7 (04):
  • [5] Text Mining and Real-Time Analytics of Twitter Data: A Case Study of Australian Hay Fever Prediction
    Subramani, Sudha
    Michalska, Sandra
    Wang, Hua
    Whittaker, Frank
    Heyward, Benjamin
    HEALTH INFORMATION SCIENCE (HIS 2018), 2018, 11148 : 134 - 145
  • [6] Twitter and Research: A Systematic Literature Review Through Text Mining
    Karami, Amir
    Lundy, Morgan
    Webb, Frank
    Dwivedi, Yogesh K.
    IEEE ACCESS, 2020, 8 (08): : 67698 - 67717
  • [7] A Big Data Case Study in Digital Humanities: Creating a Performance Benchmark for Canonical Text Services
    Heyer, Gerhard
    Tiepmar, Jochen
    Datenbank-Spektrum, 2019, 19 (01): : 41 - 49
  • [8] Impact of COVID-19: A Text Mining Analysis of Twitter Data in Spanish Language
    Osakwe, Zainab Toteh
    Cortes, Yamnia, I
    HISPANIC HEALTH CARE INTERNATIONAL, 2021, 19 (04) : 239 - 245
  • [9] Twitter trends in #Parasitology determined by text mining and topic modelling
    Ellis, John T.
    Reichel, Michael P.
    CURRENT RESEARCH IN PARASITOLOGY & VECTOR-BORNE DISEASES, 2023, 4
  • [10] Text Mining Digital Humanities Projects: Assessing Content Analysis Capabilities of Voyant Tools
    Miller, A.
    JOURNAL OF WEB LIBRARIANSHIP, 2018, 12 (03) : 169 - 197