An Analysis of Slant in Tweets
| Autor: | Nagaraju Vadranam, Starla Marier Demings, K. M. George |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
Computer science business.industry Supervised learning Sentiment analysis 02 engineering and technology Construct (python library) computer.software_genre Set (abstract data type) 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Social media Artificial intelligence Cluster analysis business computer Natural language processing Reliability (statistics) |
| Zdroj: | BDCAT |
| DOI: | 10.1145/3365109.3368770 |
| Popis: | Determination of quality and reliability of information found in social media have been subjects of study by sever researchers. One set of solution may not work in all cases. This paper presents a method to estimate the slant of tweets related to a topic. The general approach followed is to construct labeled data from tweets and use supervised learning to build predictive models. Results obtained from two datasets are compared against OTC model and a CNN based model. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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