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June 1, 2016Cognitive Computation291 citationsOpen Access

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

KDKia DashtipourSPSoujanya PoriaAHAmir Hussain

Key Points

  • The aim is to review current multilingual sentiment analysis techniques and evaluate their practical performance.
  • Performed a state-of-the-art review of existing multilingual sentiment analysis approaches.
  • Implemented various techniques on common datasets for direct comparison.
  • Evaluated and discussed the precision and reproducibility of findings reported by original authors.
  • Observed precision in experiments was lower than originally reported, suggesting implementation challenges.
  • Found discrepancies due to insufficient detail in original method presentations, impacting reproducibility.
  • Highlighted the need for better definitions and implementations in sentiment analysis research.

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.

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Cite This Study

Dashtipour et al. (2016) studied this question.

synapsesocial.com/papers/69d9d1f25e5bcb4e3b837ee6https://doi.org/10.1007/s12559-016-9415-7
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