Adaptation of Semantic Rule-Based Sentiment Analysis Approach for Russian Language

In this digital era, people are very keen to share their feedback about any product, services, or current issues on social networks and other platforms. A fine analysis of these feedbacks can give a clear picture of what people think about a particular topic. This work proposed an almost unsupervised Aspect Based Sentiment Analysis approach for textual reviews. Latent Dirichlet Allocation, along with linguistic rules, is used for aspect extraction. Aspects are ranked based on their probability distribution values and then clustered into predefined categories using frequent terms with domain knowledge. SentiWordNet lexicon uses for sentiment scoring and classification. The experiment with two popular datasets shows the superiority of our strategy as compared to existing methods. It shows the 85% average accuracy when tested on manually labeled data.

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User-Generated Tweets about Global Green Brands: A Sentiment Analysis Approach

Market-Tržište ◽

10.22598/mt/2018.30.2.125 ◽

2018 ◽

Vol 30 (2) ◽

pp. 125-145

Author(s):

Saba Resnik ◽

Mateja Kos Koklič

Keyword(s):

Sentiment Analysis ◽

Analysis Approach

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A hybrid sentiment analysis approach using black widow optimization based feature selection

Journal of Engineering Research ◽

10.36909/jer.12039 ◽

2021 ◽

Author(s):

Anand Joseph Daniel ◽

◽

M Janaki Meena ◽

Keyword(s):

Feature Selection ◽

Sentiment Analysis ◽

Performance Metrics ◽

Computation Time ◽

Online Reviews ◽

Reduction Technique ◽

Feature Reduction ◽

Analysis Approach ◽

Black Widow ◽

Feature Selection Technique

With the massive development of Internet technologies and e-commerce technology, people rely on the product reviews provided by users through web. Sentiment analysis of online reviews has become a mainstream way for businesses on e-commerce platforms to satisfy the customers. This paper proposes a novel hybrid framework with Black Widow Optimization (BWO) based feature reduction technique which combines the merits of both machine learning and lexicon-based approaches to attain better scalability and accuracy. The scalability problem arises due to noisy, irrelevant and unique features present in the extracted features from proposed approach, which can be eliminated by adopting an effective feature reduction technique. In our proposed BWO approach, without changing the accuracy (90%), the feature-set size is reduced up to 43%. The proposed feature selection technique outperforms other commonly used Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) based feature selection techniques with reduced computation time of 21 sec. Moreover, our sentiment analysis approach is analyzed using performance metrics such as precision, recall, F-measure, and computation time. Many organizations can use these online reviews to make well-informed decisions towards the users’ interests and preferences to enhance customer satisfaction, product quality and to find the aspects to improve the products, thereby to generate more profits.

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Rule Based Morphological Variation Removable Stemming Algorithm

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c6200.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 1809-1814

Keyword(s):

Feature Selection ◽

Sentiment Analysis ◽

Morphological Variation ◽

Morphological Changes ◽

The Internet ◽

Rule Based ◽

The People ◽

Stop Word ◽

Preprocessing Technique ◽

Better Than

Sentiment analysis is a technique to analyze the people opinion, attitude, sentiment and emotion towards any particular object. Sentiment analysis has the following steps to predict the opinion of a review sentences. The steps are preprocessing, feature selection, classification and sentiment prediction. Preprocessing is the main important step and it consists of many techniques. They are Stop word Removal, punctuation removal, conversion of numbers to number names. Stemming is another important preprocessing technique which is used to transform the words in text into their grammatical root form and is mainly used to improve the retrieval of the information from the internet. It is applied mainly to get strengthen the retrieval of the information. Many morphological languages have immense amount of morphological deviation in the words. It triggered vast challenges. Many algorithms exist with different techniques and has several drawbacks. The aim of this paper is to propose a rule based stemmer that is a truncating stemmer. The new stemming mechanism in this paper has brought about many morphological changes. The new rule based morphological variation removable stemming algorithm is better than the existing other algorithms such as New Porter, Paice/Lovins and Lancaster stemming algorithm

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