NLP Case Study
How Topic Modeling helped a client find hostile topics among various social media data
Problem:
The client a consumer tech company based in USA, wanted to identify hostile topics emerging out of their social media data. The client had pages on different social media platforms and wanted a deeper insight into the hostile or negative topics being associated with their brand.
Solution:
- Topic Modeling and other Natural Language Processing algorithms were used to identify several topics from social media posts and comments, across different geographies for a specific time period.
- Topic models are a family of statistical-based algorithms to summarize, explore and index large collections of text documents.1 Latent Dirichlet Allocation approach was used to identify several topics emerging out of social media conversations.
Impact
Through the topic models we were able to provide the client a list of top negative topics being associated with the brand.
The topics helped client to understand customer pain points better.
The client decided to enhance their customer support system post this exercise.
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