Autor/Autorin: Kaur Sukhpreet
Sukhpreet Kaur has completed her MPhil from Department of Computer Science, Punjabi University, Patiala. She is NET qualified and currently working as Assistant Programmer in Jagat Guru Nanak Dev Punjab State Open University, Patiala.
Code-mixed language is very commonly used in today´s multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared.
Code-mixed language is very commonly used in today's multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared.
Klappentext
Code-mixed language is very commonly used in today¿s multilingual society. It is the phenomenon of mixing the syntax and vocabulary of many languages in single sentence. Sentiment analysis of code-mixed language aims at identifying the polarity value of the sentence. This book mainly focuses on sentiment analysis of code-mixed Tweets consisting of words from Hindi and English language and it also contains other symbols. The developed system is used to detect the polarity/sentiment value of a tweet where the value of polarity can be positive, negative or neutral. Various experiments are carried out on a dataset of Tweets using different models. Results of different models are evaluated and compared.
