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Singh, Mukhtiar
- Sentiment Analysis of Code Mixed Text Consisting of English- Punjabi Lexicon
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Authors
Affiliations
1 Department o f Computer Science, Punjabi University, Patiala, IN
2 School o f Management Studies, Punjabi University, Patiala, IN
1 Department o f Computer Science, Punjabi University, Patiala, IN
2 School o f Management Studies, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 33 (2020), Pagination: 15-23Abstract
Sentiment analysis is a field of study for analyzing emotions of people such as happy, sad, angry, etc. towards the entities and attributes expressed in written text. In this study, the data was collected in the textual form from different sources like Facebook, YouTube, Twitter, and Whatsapp, then pre-processed the collected data. After that, identification of the language of code-mixed text performed, which includes tokenization, word-play, misspelled words, abbreviations, slang words, phonetic-typing, etc. After the identification task, the English-Punjabi dictionary was created which was consisting of opinionated words list like positive, negative, and neutral words list. The rest of the words are being stored in an unsorted word list. In the last, a statistical technique applied at sentence level sentiment polarity of the English-Punjabi code mixed dataset. It was identified that the results up to the Five-Grams and Tri-Grams approaches had the similarity.Keywords
Code Mixed Text, Romanized Text, Natural Language Processing, Text Processing, Romanized Text, Sentiment Analysis, Microblogging.Full Text
References
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- Twitter Opinion Analysis about 5G Technology
Abstract Views :285 |
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Authors
Affiliations
1 Ph.D. Research Scholar, Department of Computer Science, Punjabi University, Patiala, IN
1 Ph.D. Research Scholar, Department of Computer Science, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 34 (2021), Pagination: 14-27Abstract
Since thousands of users freely express their opinions on Twitter every day, it has become a rich source for sentiment analysis and opinion mining data. In this investigation, we look at the sentiment of shared articles with the hashtag "#5G" and categories it as positive, negative, or neutral. We used statistical sentiment analysis tool to create a classification model that had an accuracy and recall of 83.69%. The findings indicate that it is possible to recognize key public opinion factors in the acceptance or rejection of 5G technology, which is valuable information for technology companies.Keywords
Twitter, Sentiment Analysis, 5G Technology.Full Text
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