Proximity-based sentiment analysis

Hasan, Shohedul; Adjeroh, Donald A.

doi:10.1109/icadiwt.2011.6041410

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…In [9], the authors proposed a new methodology for sentiment analysis called proximity-based sentiment analysis. They performed sentiment classification using only the proximity based features for the analysis of movie reviews.…”

Section: Literature Surveymentioning

confidence: 99%

The Various Approaches for Sentiment Analysis: A Survey

2016

IJSR

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Sentiment analysis or Opinion mining is a machine learning approach in which machines analyze and classify the human's sentiments which are expressed in the form of either text or speech. The textual reviews available in the web are increasing day by day. Manual analysis of such large number of reviews is practically impossible. Therefore, sentiment analysis can be used to mine the overall sentiment or opinion polarity from the texts. The sentiment analysis finds its application in movie reviews, blogs, customer feedback, twitter etc. This literature survey is the study of various approaches/methods that can be used to classify the reviews.

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Section: Literature Surveymentioning

confidence: 99%

The Various Approaches for Sentiment Analysis: A Survey

2016

IJSR

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“…A proximity-based sentiment analysis is proposed by Hasan et al [7] that uses features based on word proximities within a sentence. The authors used three proximity-based features which are called proximity distribution, mutual information between proximity types, and proximity patterns.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is a semi-supervised sentiment estimation technique which lacks multi-lingual sentiment analysis as well as the criteria/procedure that indicates when to smooth the polarity estimates. The major area of focus of the techniques proposed by Hasan and Adjeroh [7] is based on sentiment analysis and text mining. The technique used proximity-based sentiment analysis.…”

Section: Critical Analysismentioning

confidence: 99%

“…It is really hard for the computing machines to automatically extract the meaning and tone of content as people express so many things in many different ways and styles etc. Sentiment analyses can prove very useful when we analyze search engine results, different blogs, social networks, web forums, different review of people on books, movies, sport and products etc [7]. This can help reduce the efforts required to go through large amount of documents to generate an opinion about the nature of the contents.…”

Section: Introductionmentioning

confidence: 99%

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A Study of Sentiment and Trend Analysis Techniques for Social Media Content

Mehmood¹,

Palli²,

Khan³

2014

IJMECS

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The social media networks have evolved rapidly and people frequently use these services to communicate with others and express themselves by sharing opinions, views, ideas etc. on different topics. The social media trend analysis is generally carried out by sifting the corresponding or interlinked events discussed on social media websites such as Twitter, Facebook etc. The fundamental objective behind such analyses is to determine the level of criticality with respect to criticism or appreciation described in the comments, tweets or blogs. The trend analysis techniques can also be systematically exploited for opinion making among the masses at large. The results of such analyses show how people think, assess, orate and opine about different issues. This paper primarily focuses on the trend detection and sentiment analysis techniques and their efficacy in the contextual information. We further discuss these techniques which are used to analyze the sentiments expressed within a particular sentence, paragraph or document etc. The analysis based on sentiments can pave way for automatic trend analysis, topic recognition and opinion mining etc. Furthermore, we can fairly estimate the degree of positivity and negativity of the opinions and sentiments based on the content obtained from a particular social media.

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“…Unary and binary AAN algorithms are also mentioned in the work. Another new approach is a proximity based sentiment analysis [14].…”

Section: Opinion Mining and Sentiment Analysismentioning

confidence: 99%

A Survey on Sentiment Analysis and Opinion Mining

Varghese¹,

Jayasree²

2013

IJRET

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Sentiment analysis is a machine learning approach in which machines analyze and classify the human's sentiments, emotions, opinions etc about some topic which are expressed in the form of either text or speech. The textual data available in the web is increasing day by day. In order to enhance the sales of a product and to improve the customer satisfaction, most of the on-line shopping sites provide the opportunity to customers to write reviews about products. These reviews are large in number and to mine the overall sentiment or opinion polarity from all of them, sentiment analysis can be used. Manual analysis of such large number of reviews is practically impossible. Therefore automated approach of a machine has significant role in solving this hard problem. The major challenge of the area of Sentiment analysis and Opinion mining lies in identifying the emotions expressed in these texts. This literature survey is done to study the sentiment analysis problem in-depth and to familiarize with other works done on the subject.

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Proximity-based sentiment analysis

Cited by 14 publications

References 20 publications

The Various Approaches for Sentiment Analysis: A Survey

The Various Approaches for Sentiment Analysis: A Survey

A Study of Sentiment and Trend Analysis Techniques for Social Media Content

A Survey on Sentiment Analysis and Opinion Mining

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