Text Mining of Twitter data for Mapping the Digital Humanities Research Trends

A case study

Keywords: Digital Humanities, twitter, Big data, Text mining, Python, Tweets


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 analysed 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 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.


How to Cite
Sawale, A. (2023). Text Mining of Twitter data for Mapping the Digital Humanities Research Trends. DESIDOC Journal of Library & Information Technology, 43(04), 258-265. https://doi.org/10.14429/djlit.43.04.19236