Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques

Citation

Dashtipour K, Poria S, Hussain A, Cambria E, Hawalah AYA, Gelbukh A & Zhou Q (2016) Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques. Cognitive Computation, 8 (4), pp. 757-771. https://doi.org/10.1007/s12559-016-9415-7

Abstract
With the advent of Internet, people actively express their opinions about products, services, events, political parties, etc., in social media, blogs, and website comments. The amount of research work on sentiment analysis is growing explosively. However, the majority of research efforts are devoted to English-language data, while a great share of information is available in other languages. We present a state-of-the-art review on multilingual sentiment analysis. More importantly, we compare our own implementation of existing approaches on common data. Precision observed in our experiments is typically lower than the one reported by the original authors, which we attribute to the lack of detail in the original presentation of those approaches. Thus, we compare the existing works by what they really offer to the reader, including whether they allow for accurate implementation and for reliable reproduction of the reported results.

Keywords
Artificial intelligence; Natural language processing; Opinion mining; Sentic computing; Sentiment Analysis

Journal
Cognitive Computation: Volume 8, Issue 4