Negation Handling in Sentiment Analysis at Sentence Level
Umar Farooq,Hassan Mansour,Antoine Nongaillard,Yacine Ouzrout,Muhammad Abdul Qadir +4 more
- Vol. 12, pp 470-478
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This article is published in International Conference on Information Management.The article was published on 2017-01-01 and is currently open access. It has received 46 citations till now. The article focuses on the topics: Sentiment analysis & Sentence.read more
Citations
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Journal ArticleDOI
Lexicon-based approach outperforms Supervised Machine Learning approach for Urdu Sentiment Analysis in multiple domains
TL;DR: It is concluded that the Lexicon-based approach outperforms Supervised Machine Learning approach not only in terms of Accuracy, Precision, Recall and F-measure but also in termsof economy of time and efforts used.
Journal ArticleDOI
Enhanced Twitter Sentiment Analysis Using Hybrid Approach and by Accounting Local Contextual Semantic
Itisha Gupta,Nisheeth Joshi +1 more
TL;DR: Experimental results show that the contextual-based SWN feature vector obtained through shiftPolarity approach alone led to an improved Twitter sentiment analysis system that outperforms the traditional reverse polarity approach by 2–6%.
Journal ArticleDOI
Managing Marketing Decision-Making with Sentiment Analysis: An Evaluation of the Main Product Features Using Text Data Mining
TL;DR: This work is able to improve recommender systems by using positive, neutral, and negative customer opinions and by classifying customers based on their comments, and proves the validity of the approach in a case study using big data extracted from Amazon online reviews, obtaining satisfactory and promising results.
Journal ArticleDOI
Effect of Negation in Sentences on Sentiment Analysis and Polarity Detection
Partha Mukherjee,Youakim Badr,Shreyesh Doppalapudi,Satish M. Srinivasan,Raghvinder S. Sangwan,Rahul Sharma +5 more
TL;DR: In this paper, a novel end-to-end sentiment analysis approach was proposed to handle negations, along with the inclusion of negation identification and negation scope marking, which achieved the best accuracy of 95.67% when combined with negation marking processing, exceeding its accuracy without any identification of negative sentences.
Journal ArticleDOI
The Impact of Translating Resource-Rich Datasets to Low-Resource Languages Through Multi-Lingual Text Processing
Abdul Ghafoor,Ali Shariq Imran,Sher Muhammad Daudpota,Zenun Kastrati,Abdullah,Rakhi Batra,Mudasir Ahmad Wani +6 more
TL;DR: In this paper, the effect of translation on the sentiment classification task from a resource-rich language to a low-resource language was evaluated and the correlation between the language with similar roots was found.
References
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Proceedings ArticleDOI
Thumbs up? Sentiment Classification using Machine Learning Techniques
TL;DR: This work considers the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative, and concludes by examining factors that make the sentiment classification problem more challenging.
Proceedings ArticleDOI
Extracting Product Features and Opinions from Reviews
Ana-Maria Popescu,Oren Etzioni +1 more
TL;DR: Opine is introduced, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across products.
Journal ArticleDOI
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
TL;DR: The goal of this work is to automatically distinguish between prior and contextual polarity, with a focus on understanding which features are important for this task, and it is shown that the presence of neutral instances greatly degrades the performance of features for distinguishing between positive and negative polarity.
Proceedings Article
Sentiment Analysis: Adjectives and Adverbs are better than Adjectives Alone
Farah Benamara,Carmine Cesarano,Antonio Picariello,Diego Reforgiato Recupero,V. S. Subrahmanian +4 more
TL;DR: This work proposes an AAC-based sentiment analysis technique that uses a linguistic analysis of adverbs of degree that leads to higher accuracy based on Pearson correlation with human subjects and describes the results of experiments.
Journal ArticleDOI
English grammar : a function-based introduction
TL;DR: In this article, the semantics of event integration, the syntax of clause integration modality verbs for-to complements "if" complements WH-complements post-posed P-C-U verbs non-verbal predicates with verbal complements.