Analyzing Topic Dynamics, Sentiments, and Semantic Coherence in Reddit Discussions on Agile and Digital Transformation
In this paper, we will discuss semantic dynamics, topical structures, and sentiment patterns of discussions on Agile methodologies and Digital Transformation in the Reddit community. Using advanced natural language processing techniques, we analyze a dataset of 3,777 Reddit posts, which were filtered and preprocessed in detail to extract meaningful insights while mitigating noise. This study uses Latent Dirichlet Allocation for topic modeling and evaluates the coherence of generated topics to ensure interpretability and relevance. Key topics identified include Agile practices, cognitive and team dynamics, digital platforms, project management, and business applications. Complementarily, VADER has been used to carry out sentiment analysis, revealing the emotional tone and sentiment polarity expressed in the discussions. This two-tier analysis will provide not only the thematic focus of the conversations but also the prevailing attitudes and perceptions surrounding Agile and Digital Transformation practices. These findings reflect the power of communitydriven narratives in shaping organizational strategies and point out emergent trends in Agile frameworks and Digital Transformation. By integrating topic modeling and sentiment analysis, this research offers actionable insights for practitioners, researchers, and decision-makers in pursuit of leveraging Agile methodologies for successful Digital Transformation initiatives.
Authors
- Blerta Abazi Chaushi (ORCID: https://orcid.org/0000-0002-1959-5492)
- Florenc Hidri (ORCID: https://orcid.org/0000-0001-8455-5430)
- Gladiola Tigno (ORCID: https://orcid.org/0000-0001-6915-0232)
Institutions
- European University of Tirana (AL)
- South East European University (MK)
Publication Details
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1109/mipro65660.2025.11131795
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00