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

Abstract

With the advent of the 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 state-of-the-art approaches on common data. Precision observed in our experiments is typically lower than that reported by the original authors, which we attribute to 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.The online version of the original article can be found under

Aspect Based Sentiment Analysis of Ridesharing Platform Reviews for Kansei Engineering

“…There is a dire need to work on multilingual reviews to extract users' true sentiments. As a result, multilingual sentiment analysis is gaining attention in Chinese, Spanish, Arabic, German, Italian, French, Japanese, Malay, Urdu, and Romanian languages along with English [34]- [36]. For example, Babelsenticnet [37] is a concept level knowledgebase for multilingual sentiment analysis that provides support for more than forty languages including Hindi/Urdu.…”