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مدیریت فناوری اطلاعات، جلد ۱۲، شماره ۴، صفحات ۱۰۵-۱۲۰
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عنوان انگلیسی Sentiment Analysis of Social Networking Data Using Categorized Dictionary
چکیده انگلیسی مقاله Sentiment analysis is the process of analyzing a person’s perception or belief about a particular subject matter. However, finding correct opinion or interest from multi-facet sentiment data is a tedious task. In this paper, a method to improve the sentiment accuracy by utilizing the concept of categorized dictionary for sentiment classification and analysis is proposed. A categorized dictionary is developed for the sentiment classification and further calculation of sentiment accuracy. The concept of categorized dictionary involves the creation of dictionaries for different categories making the comparisons specific. The categorized dictionary includes words defining the positive and negative sentiments related to the particular category. It is used by the mapper reducer algorithm for the classification of sentiments. The data is collected from social networking site and is pre-processed. Since the amount of data is enormous therefore a reliable open-source framework Hadoop is used for the implementation. Hadoop hosts various software utilities to inspect and process any type of big data. The comparative analysis presented in this paper proves the worthiness of the proposed method.
کلیدواژه‌های انگلیسی مقاله Hadoop,Big data,HDFS,Map-Reduce,Facepager,Sentiment analysis
نویسندگان مقاله Akansha Singh |
Associate Prof., Department of CSE, ASET, Amity University Uttar Pradesh, Noida.

Aastha Sharma |
The North Cap University, Gurgaon, India.

Krishna Kant Singh |
Associate Prof., Department of ECE, KIET Group of Institutions, Ghaziabad, India.

Anuradha Dhull |
Assistant Prof., The North Cap University, Gurgaon, India.

نشانی اینترنتی https://jitm.ut.ac.ir/article_78402_d5d943afd9753b7ce691d4d0be85e122.pdf
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