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
  • [21] A Text-Mining Analysis of Research Trends in Animal-Assisted Therapy
    Lee, Shin-Ja
    Kim, Geun-Hyeon
    Moon, Yea-Hwang
    Lee, Sung-Sill
    ANIMALS, 2023, 13 (19):
  • [22] A Case Study of Data Quality in Text Mining Clinical Progress Notes
    Berndt, Donald J.
    Mccart, James A.
    Finch, Dezon K.
    Luther, Stephen L.
    ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS, 2015, 6 (01)
  • [23] Text Mining Based GPT Method for Analyzing Research Trends
    Ha, Jeong-Hoon
    Lee, Dong-Hee
    Choi, Bong-Jun
    INTELLIGENT HUMAN COMPUTER INTERACTION, IHCI 2023, PT I, 2024, 14531 : 26 - 31
  • [24] Analyzing Community Care Research Trends Using Text Mining
    Park, Yoonseo
    Park, Sewon
    Lee, Munjea
    JOURNAL OF MULTIDISCIPLINARY HEALTHCARE, 2022, 15 : 1493 - 1510
  • [25] Text Mining the Variety of Trends in the Field of Simulation Modeling Research
    Jadric, Mario
    Mijac, Tea
    Cukusic, Maja
    PERSPECTIVES IN BUSINESS INFORMATICS RESEARCH, BIR 2020, 2020, 398 : 143 - 158
  • [26] Research trends in CISTI's unveiled through text mining
    Moro, Sergio
    Alturas, Braulio
    Esmerado, Joaquim
    Costa, Carlos J.
    2017 12TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2017,
  • [27] TRENDS IN BUSINESS STRATEGY RESEARCH, BIBLIOMETRIC ANALYSIS AND TEXT MINING
    Dvorak, Jiri
    Tripes, Stanislav
    Sokolova, Marcela
    Musilova, Iveta
    JOURNAL OF BUSINESS ECONOMICS AND MANAGEMENT, 2022, 23 (06) : 1377 - 1397
  • [28] Uncovering Research Streams in the Data Economy Using Text Mining Algorithms
    Azkan, Can
    Spiekermann, Markus
    Goecke, Henry
    TECHNOLOGY INNOVATION MANAGEMENT REVIEW, 2019, 9 (11): : 62 - 74
  • [29] Development and evaluation of an automatic text annotation system for supporting digital humanities research
    Chen, Chih-Ming
    Chen, Yung-Ting
    Liu, Chen-Yu
    LIBRARY HI TECH, 2019, 37 (03) : 436 - 455
  • [30] Noise Annoyance in the UAE: A Twitter Case Study via a Data-Mining Approach
    Peplow, Andrew
    Thomas, Justin
    AlShehhi, Aamna
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (04) : 1 - 10