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Full-Text Articles in Physical Sciences and Mathematics
Semtiment Analysis On Youtube: A Brief Survey, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Afsana Khan
Semtiment Analysis On Youtube: A Brief Survey, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Afsana Khan
Dr. Muhammad Zubair Asghar
Sentiment analysis or opinion mining is the field of study related to analyze opinions, sentiments, evaluations, attitudes, and emotions of users which they express on social media and other online resources. The revolution of social media sites has also attracted the users towards video sharing sites, such as YouTube. The online users express their opinions or sentiments on the videos that they watch on such sites. This paper presents a brief survey of techniques to analyze opinions posted by users about a particular video.
Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi
Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi
Dr. Muhammad Zubair Asghar
One of the most thrived features of the Web 2.0 era is the fastest growing of user-generated content in the shape of blogs and reviews, with unmatched speed and size. These reviews contain poor, text quality and structure which results spelling mistakes as well as out-of-vocabulary words. This paper presents a Context-Aware Spelling Corrector for Sentiment Analysis based on similarity measures and statistical language model. The paper also presents some compelling statistics about spelling errors. The comparative results show that the proposed framework outperforms the related systems, features wise and in accuracy.
Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.
Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar
Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
With the advent of web, online user reviews are getting more and more attention of the researchers because valuable information about products and services are available on social media like twitter1. These reviews are very helpful for organizations as well as for new customers showing interest in these products or services. But this data is generated in tremendous amount which is out of control of manual mining methods. These reviews need a model that has the ability to gauge these shared reviews according to predefined categories. This work introduces a rule based approach to find the opinion classification of reviews. …
Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar
Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
The online information explosion has created great challenges and opportunities for both information producers and consumers. Understanding customer’s feelings, perceptions and satisfaction is a key performance indicator for running successful business. Sentiment analysis is the digital recognition of public opinions, feelings, emotions and attitudes. People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources. The comparative results …
Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan
Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan
Dr. Muhammad Zubair Asghar
Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual …