Twitter Sentiment Analysis - The Good the Bad and the OMG!
In this paper, we investigate the utility of linguistic features for detecting the sentiment of Twitter messages. We evaluate the usefulness of existing lexical resources as well as features that capture information about the informal and creative language used in microblogging. We take a supervised approach to the problem, but leverage existing hashtags in the Twitter data for building training data.
In this paper, we investigate the utility of linguistic features for detecting the sentiment of Twitter messages. We evaluate the usefulness of existing lexical resources as well as features that capture information about the informal and creative language used in microblogging. We take a supervised approach to the problem, but leverage existing hashtags in the Twitter data for building training data.
- Type of material
- Terms of use
- Target audience
- Subject areas
- Tags
- Languages
- Media formats
- Accessibility features
- OER type
- Metadata and document(s)
Submitted by
Valentina Seminara
25/05/2020
in the project 4. What sentiment analysis is today? How Lords of Data profile our emotions
last updated 25/05/2020
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