Open AccessSentiment Categorization through Natural Language Processing : A Survey
Author(s) -
Jyovita Christi,
Gayatri Jain
Publication year - 2019
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset196626
Subject(s) - sentiment analysis , categorization , computer science , feeling , feature (linguistics) , natural (archaeology) , data science , the internet , social media , natural language processing , artificial intelligence , psychology , world wide web , linguistics , social psychology , history , philosophy , archaeology
Sentiment is an attitude, thought, or judgment prompted by feeling. Sentiment analysis, which is also known as opinion mining, studies people’s sentiments towards certain entities. Sentiment Analysis isn’t an unfamiliar term anymore. Today, smart phones, high speed Internet and various forums and social networks, have made it very common for people to give voice to their opinions. Therefore, a lot of textual data is available in various forms where people express their opinions. Analysing this data to know the underlying sentiment behind it has also become quite popular these days. Various techniques and applications have been created in the past and even today to perform sentiment analysis. This paper contributes towards understanding some of the modern techniques and in knowing which technique to use under what circumstances. It also studies feature extraction which is an important aspect of sentiment analysis. Feature extraction allows us to identify the features in the given text and analyse the sentiment for each feature.