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
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] Using Text Mining Techniques to Identify Research Trends: A Case Study of Design Research
    Nie, Binling
    Sun, Shouqian
    APPLIED SCIENCES-BASEL, 2017, 7 (04):
  • [3] Text data mining: A case study
    Ford, CW
    Chiang, CC
    Wu, H
    Chilka, RR
    Talburt, JR
    ITCC 2005: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: CODING AND COMPUTING, VOL 1, 2005, : 122 - 127
  • [4] A social network analysis of Twitter: Mapping the digital humanities community
    Grandjean, Martin
    COGENT ARTS & HUMANITIES, 2016, 3
  • [5] Collaborative Digital Research: Case Study of Text Mining a Corpus of Academic Journals
    Baillargeon, Tara
    Kowalik, Eric
    Cook, Jennifer M.
    NEW REVIEW OF ACADEMIC LIBRARIANSHIP, 2021, 27 (02) : 230 - 242
  • [6] From digital library to digital government: A case study in crime data mapping and mining
    Chen, HC
    DIGITAL LIBRARIES: PEOPLE, KNOWLEDGE, AND TECHNOLOGY, PROCEEDINGS, 2002, 2555 : 36 - 52
  • [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] 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
  • [9] On the Way to a missed Opportunity Musicology, Law and the Core Business of Digital Humanities: Text and Data Mining
    Doehl, Frederic
    LIED UND POPULARE KULTUR-SONG AND POPULAR CULTURE, 2020, 65 : 243 - 266
  • [10] Research trends on big data domain using text mining algorithms
    Jalali, Seyed Mohammad Jafar
    Park, Han Woo
    Vanani, Iman Raeesi
    Kim-Hung Pho
    DIGITAL SCHOLARSHIP IN THE HUMANITIES, 2021, 36 (02) : 361 - 370