Making sense of electrical vehicle discussions using sentiment analysis on closely related news and user comments
This work addresses sentiment analysis for electric vehicle stakeholders, but it is incremental as it applies existing methods to new data without major methodological innovations.
The study tackled the problem of understanding sentiment in electric vehicle discussions by applying token-wise and document-wise sentiment analysis to news and user comments, finding a statistically significant difference in sentiment between groups at the token level but no significant difference at the document level.
We used a token-wise and document-wise sentiment analysis using both unsupervised and supervised models applied to both news and user reviews dataset. And our token-wise sentiment analysis found a statistically significant difference in sentiment between the two groups (both of which were very large N), our document-wise supervised sentiment analysis found no significant difference in sentiment.