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Sentiment analysis of text documents is a very important part of contemporary text mining. The purpose of this article is to present a new technique of text sentiment analysis which can be used with any type of a document-sentiment-classification method. The proposed technique involves feature selection independently of a classifier, which reduces the size of the feature space. Its advantages include...
Social media serves as a unified platform for users to express their thoughts on subjects ranging from their daily lives to their opinion on consumer brands and products. These users wield an enormous influence in shaping the opinions of other consumers and influence brand perception, brand loyalty and brand advocacy. In this paper, we analyze the opinion of 19M Twitter users towards 62 popular industries,...
In order to explore the semantic clues and online shopping consumer behavior rules contain online shopping commentary, this paper takes 55560 after-sales evaluation as the research object to put forward the netizens related hypothesis evaluation of social network evolution, and evaluation of innovation of Internet users social network evolution diagram visualization description and empirical analyses...
In this work sentiment analysis of annual budget for Financial year 2016–17 is done. Text mining is used to extract text data from the budget document and to compute the word association of significant words and their correlation in computed with the associated words. Word frequency and the corresponding word cloud is plotted. The analysis is done in R software. The corresponding sentiment score is...
In this paper, we propose a interactive constrained independent topic analysis in text mining. Independent Topic Analysis (ITA) is a method for extracting the independent topics from the document data by using the independent component analysis. In the independent topic analysis, it is possible to extract the most independent topics between each topic. By extracting the independent topic, it is easy...
The deep transformation induced by the World Wide Web (WWW) revolution has thoroughly impacted a relevant part of the social interactions in our present global society. The huge amount of unstructured information available on blogs, forum and public institution web sites puts forward different challenges and opportunities. Starting from these considerations, in this paper we pursue a two-fold goal...
Considerable research efforts have been devoted to Twitter sentiment analysis in recent years. Given the informal writing style of Twitter, there exists an endless variety of sound vocabulary, slogans, emoticons and special characters that can be used to express one's opinion in a maximum of 140-characters. This results in a sparsity problem making the training of machine learning classifiers from...
Personally Identifiable Information (PII) includes any information that can be used to distinguish or trace an individual’s identity such as name, social security number, date and place of birth, mother’s maiden name, or biometric records. It also includes other information that is linked or linkable to an individual, such as medical, educational, financial, and employment information. PII is often...
Over the recent years, there has been a growing interest in developing new research evaluation methods that could go beyond the traditional citation-based metrics. This interest is motivated on one side by the wider availability or even emergence of new information evidencing research performance, such as article downloads, views and Twitter mentions, and on the other side by the continued frustrations...
In this paper, a new identification technique based on a Kendal Rank Correlation Model is described. The method is based on the exploitation of a text vector model in the area of the text similarity detection issue. This study is divided into two stages: In the first stage the Text Vector Model (TVM) is described. In the second stage the Kendal rank correlation coefficients, which are obtained from...
Communities of learning face two major problems for his development, low quality and quantity of participation and information overload due to high amount of participation. These two problem can be solved by giving instant feedback and ordering the data available in the online environment. This work presents an automatic method to evaluate and quantificate participation in order to score messages...
Technologies play an important role in the survival and development of enterprises. Understanding and monitoring the core technological components (e.g., technology process, operation method, function) of a technology is an important issue for researchers to develop R&D policy and manage product competitiveness. However, it is difficult to identify core technological components from a mass of...
This paper aims to analyze affective expressions in articles of popular science by text mining with the keywords “Cancer” and “Immunity”. This study selects 145 articles from the website of a magazine and segmented them into 410,919 terms. And the study uses an automatic system to classify the terms into vocabulary categories, selecting the affective terms with specific vocabulary categories. The...
Sentiment analysis emerged as an important computational domain to gain insights from snippets of texts, as social media recently gained popularity. Text mining has long been a fundamental data analytic for sentiment analysis. One of the popular preprocessing approaches in text mining is transforming text strings to word vectors which form a high-dimensional sparse matrix. This sparse matrix poses...
The Patient Health Questionnaire (PHQ-9) is the depression module, which provides a score correlating to each of the Depression Severity Measure (DSM-IV) criteria, whose output is a total score suggesting which category of depression a patient slots into. In this paper we propose a novel method to potentially improve the current system in place for health professionals in diagnosing depression. Thus,...
For the question of information security vulnerabilities discovery, the parallel vulnerabilities discovery method is given based on the CAPEC, CWE, CVE and other open source database and text mining. Firstly, we can extract the association vulnerability CWE under the same attack mode, then from CWE associated with CVE based on open source database. That can help us to analyze the potential parallel...
Social media is widely used as a channel of communication in general purposes, including the comment that are related to retail business. It is a highly effective communication tool for direct interacting with their customers. Growth rate of the users is rapidly increasing, because they use this channel to receive information and share something interesting. In this paper, we present a comparison...
Emotions serve as a communicative function both within the brain and within the social group. Most of previous opinion mining studies applied on Arabic microblog text to identify positive, negative or neutral polarity. This paper studies the problem of detecting multiple emotion classes in Arabic microblog text (e.g. Twitter). Incoming Arabic microblog text is classified into one of fine grained emotional...
The purpose of Text Mining is to process unstructured (textual) information, extracting meaningful numeric indices from the text, and, thus, make the information contained in the text accessible to the various data mining (statistical and machine learning) algorithms. Information can be extracted to derive summaries for the words contained in the documents or to compute summaries for the documents...
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