Andere Kunden interessierten sich auch für
![Movie Rating Prediction Based on Twitter Sentiment Analysis]( "Movie Rating Prediction Based on Twitter Sentiment Analysis")
Movie Rating Prediction Based on Twitter Sentiment Analysis23,99 €![Forecast rating based on public comments by sentiment analysis]( "Forecast rating based on public comments by sentiment analysis")
Forecast rating based on public comments by sentiment analysis26,99 €![Evaluierung der Nutzung von Social Media für den Kundenservice]( "Evaluierung der Nutzung von Social Media für den Kundenservice")
Evaluierung der Nutzung von Social Media für den Kundenservice41,90 €![Ocena wykorzystania mediów spo¿eczno¿ciowych do obs¿ugi klienta]( "Ocena wykorzystania mediów spo¿eczno¿ciowych do obs¿ugi klienta")
Ocena wykorzystania mediów spo¿eczno¿ciowych do obs¿ugi klienta25,99 €![Evaluating the Use of Social Media for Customer Service]( "Evaluating the Use of Social Media for Customer Service")
Evaluating the Use of Social Media for Customer Service51,99 €![Avaliação da Utilização das Redes Sociais no Atendimento ao Cliente]( "Avaliação da Utilização das Redes Sociais no Atendimento ao Cliente")
Avaliação da Utilização das Redes Sociais no Atendimento ao Cliente25,99 €![Evaluación del uso de los medios sociales para el servicio al cliente]( "Evaluación del uso de los medios sociales para el servicio al cliente")
Evaluación del uso de los medios sociales para el servicio al cliente27,99 €
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.