A Lexical Updating Algorithm for Sentiment Analysis on Chinese Movie Reviews

Song, Yiwei; Gu, Kaiwen; Li, Huakang; Sun, Guozi

doi:10.1109/cbd.2017.40

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…These techniques have f-measurement success values of 88% and 94%, respectively (Permatasari, Fauzi, Adikara, & Lukmana Sari, 2018: 92). The study of machine learning in Hindi language (Nanda, Dua, & Nanda, 2018) and a study of a lexical update algorithm in Chinese language (Song, Gu, Li, & Sun, 2017) are other recent language-based studies.…”

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confidence: 99%

An Example of Pragmatic Analysis in Natural Language Processing: Sentimental Analysis of Movie Reviews

Sütçü¹,

Aytekin²

2019

TOJDAC

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Natural Language Processing (NLP) studies are one of the most exciting applications of artificial intelligence and it is foreseen that NLP will cause new and revolutionist changes in humancomputer interaction. In this aspect, NLP is analyzed in five different segments: Phonology, Morphology, Syntax, Semantics, Pragmatics Analysis. In this paper, a sentimental analysis will be conducted using movie reviews left by users on beyazperde.com. The sentimental analysis allows to automatically draw conclusions about the mood from text data. Thus, numerous reviews left on a movie can be sorted as a positive or negative mood without the need of reading all of them one by one. The ability to sort the reviews automatically according to their mood is invaluable to those who are considering watching the said movie, actors\actresses, producers and advertisers. Such application arms media companies with new and improvable opportunities to create effective strategies. In this aspect, viewer expectations can be analyzed, and this information can be utilized for the upcoming program projects. Importance of communications and information technologies is undeniable. It is foreseen that this paper will aid the production of information processing in Turkish.

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confidence: 99%

An Example of Pragmatic Analysis in Natural Language Processing: Sentimental Analysis of Movie Reviews

Sütçü¹,

Aytekin²

2019

TOJDAC

View full text Add to dashboard Cite

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KL-NF technique for sentiment classification

Garg

Lobiyal

2021

Multimed Tools Appl

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Improving Sentiment Classification Performance through Coaching Architectures

et al. 2022

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Intelligent systems have been developed for years to solve specific tasks automatically. An important issue emerges when the information used by these systems exhibits a dynamic nature and evolves. This fact adds a level of complexity that makes these systems prone to a noticeable worsening of their performance. Thus, their capabilities have to be upgraded to address these new requirements. Furthermore, this problem is even more challenging when the information comes from human individuals and their interactions through language. This issue happens more easily and forcefully in the specific domain of Sentiment Analysis, where feelings and opinions of humans are in constant evolution. In this context, systems are trained with an enormous corpus of textual content, or they include an extensive set of words and their related sentiment values. These solutions are usually static and generic, making their manual upgrading almost unworkable. In this paper, an automatic and interactive coaching architecture is proposed. It includes a ML framework and a dictionary-based system both trained for a specific domain. These systems converse about the outcomes obtained during their respective learning stages by simulating human interactive coaching sessions. This leads to an Active Learning process where the dictionary-based system acquires new information and improves its performance. More than 800, 000 tweets have been gathered and processed for experiments. Outstanding results were obtained when the proposed architecture was used. Also, the lexicon was updated with the prior and new words related to the corpus used which is important to reach a better sentiment analysis classification.

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A Lexical Updating Algorithm for Sentiment Analysis on Chinese Movie Reviews

Cited by 4 publications

References 16 publications

An Example of Pragmatic Analysis in Natural Language Processing: Sentimental Analysis of Movie Reviews

An Example of Pragmatic Analysis in Natural Language Processing: Sentimental Analysis of Movie Reviews

KL-NF technique for sentiment classification

Improving Sentiment Classification Performance through Coaching Architectures

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