Journal of Engineering Science and Technology Review
The arrival of e-commerce and the multitude of information presented by the web have established the internet as a principal destination for consumers looking for truthful opinions and multiple viewpoints for some product, news, topic, or trend in the markets. Thus, it is desirable to make this search easier by using systems which sift through the mass of data and summarize the available opinions for easy understanding of the seeker. This task, known as sentiment analysis, is currently a prominent area of research. Sentiment analysis can be useful for businesses, data analysts and data scientists, as well as customers. Even though many methods are designed to perform this task on English data, there is a lack of systems that can analyze data in other languages. This paper attempts to provide a detailed study on the sentiment analysis methods applied on languages other than English. The tools used, pros and cons, and efficiency of all methods is covered. The associated challenges are also discussed. The paper covers methods that analyze translated data as well as methods that analyze available data in the target language.
Sagnika, Santwana; Pattanaik, Anshuman; Mishra, Bhabani Shankar Prasad; and Meher, Saroj K., "A review on multi-lingual sentiment analysis by machine learning methods" (2020). Journal Articles. 506.
Open Access, Bronze