Word Association Thematic Analysis: Insight Discovery from the Social Web

Mike Thelwall

2022

Abstract

Billions of short messages are posted daily to the public social web. This gives opportunities for researchers to gain insights into the issues discussed, but extracting useful information can be challenging. On the one hand, the simplifying quantitative approaches for large scale analysis risk misinterpreting the patterns found because of the many different uses of the social web. On the other hand, small scale qualitative investigations may miss the big picture and ignore most of the data. This talk describes a mixed methods approach, word association thematic analysis, that attempts to gain the face validity of small-scale qualitative investigations with the power of large-scale pattern detection. The method leverages comparisons to identify sets of characteristic words for a topic, then applies thematic analysis to group these words into patterns according to the context in which they are used. The comparisons can be temporal (e.g., early vs. late tweets), topic-based (e.g., vaxxers vs. antivaxxers), or user-based (e.g., gender, location). The outcome of word association thematic analysis is a set of themes that characterise an issue in a social web site, supported by qualitative evaluations of the context of the words analysed and statistical tests for the validity of the differences identified.

Paper Citation

in Harvard Style

Thelwall M. (2022). Word Association Thematic Analysis: Insight Discovery from the Social Web. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-613-2, pages 5-10. DOI: 10.5220/0011597800003318

in Bibtex Style

@conference{webist22,
author={Mike Thelwall},
title={Word Association Thematic Analysis: Insight Discovery from the Social Web},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2022},
pages={5-10},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011597800003318},
isbn={978-989-758-613-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Word Association Thematic Analysis: Insight Discovery from the Social Web
SN - 978-989-758-613-2
AU - Thelwall M.
PY - 2022
SP - 5
EP - 10
DO - 10.5220/0011597800003318