List of Articles sentiment analysis

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  1 - Using Sentiment Analysis and Combining Classifiers for Spam Detection in Twitter
  mehdi salkhordeh haghighi Aminolah Kermani
  20.1001.1.27170411.1401.14.51.10.6
  The welcoming of social networks, especially Twitter, has posed a new challenge to researchers, and it is nothing but spam. Numerous different approaches to deal with spam are presented. In this study, we attempt to enhance the accuracy of spam detection by applying one More

  The welcoming of social networks, especially Twitter, has posed a new challenge to researchers, and it is nothing but spam. Numerous different approaches to deal with spam are presented. In this study, we attempt to enhance the accuracy of spam detection by applying one of the latest spam detection techniques and its combination with sentiment analysis. Using the word embedding technique, we give the tweet text as input to a convolutional neural network (CNN) architecture, and the output will detect spam text or normal text. Simultaneously, by extracting the suitable features in the Twitter network and applying machine learning methods to them, we separately calculate the Tweeter spam detection. Eventually, we enter the output of both approaches into a Meta Classifier so that its output specifies the final spam detection or the normality of the tweet text. In this study, we employ both balanced and unbalanced datasets to examine the impact of the proposed model on two types of data. The results indicate an increase in the accuracy of the proposed method in both datasets. Manuscript profile
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  2 - A Horizon for Sentiment Analysis in Social Networks based on Interpreting Contents
  Maryam Tayefeh Mahmoudi َAmirmansour  Yadegari Parvin Ahmadi Kambiz Badie
  Interpreting contents in social networks with the aim of analyzing the sentiment of their narrators is of particular significance. In this paper, we present a framework for such a purpose, which is able to classify the messages hidden in contents based on using some rul More

  Interpreting contents in social networks with the aim of analyzing the sentiment of their narrators is of particular significance. In this paper, we present a framework for such a purpose, which is able to classify the messages hidden in contents based on using some rule-type protocols with high abstraction level. According to this framework, items such as prosodic of a content's narrator, context of disseminating a content and the key propositions in a content's text are regarded in the condition part of a protocol, while the possible classes for the message in a content are considered as its action part. It is to be noted that the proposed rule-type protocols can equally be used for other languages due to the generic-ness of the above-mentioned items. Results of computer simulations on a variety of different contents in the social networks show that the proposed framework is sufficiently capable of analyzing the sentiment of the contents' narrators in these networks. Manuscript profile
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  3 - Liquidity Risk Prediction Using News Sentiment Analysis
  hamed mirashk albadvi albadvi mehrdad kargari Mohammad Ali Rastegar Mohammad Talebi
  20.1001.1.27170411.1402.15.55.14.5
  One of the main problems of Iranian banks is the lack of risk management process with a forward-looking approach, and one of the most important risks in banks is liquidity risk. Therefore, predicting liquidity risk has become an important issue for banks. Conventional m More

  One of the main problems of Iranian banks is the lack of risk management process with a forward-looking approach, and one of the most important risks in banks is liquidity risk. Therefore, predicting liquidity risk has become an important issue for banks. Conventional methods of measuring liquidity risk are complex, time-consuming and expensive, which makes its prediction far from possible. Predicting liquidity risk at the right time can prevent serious problems or crises in the bank. In this study, it has been tried to provide an innovative solution for predicting bank liquidity risk and leading scenarios by using the approach of news sentiment analysis. The news sentiment analysis approach about one of the Iranian banks has been used in order to identify dynamic and effective qualitative factors in liquidity risk to provide a simpler and more efficient method for predicting the liquidity risk trend. The proposed method provides practical scenarios for real-world banking risk decision makers. The obtained liquidity risk scenarios are evaluated in comparison with the scenarios occurring in the bank according to the guidelines of the Basel Committee and the opinion of banking experts to ensure the correctness of the predictions and its alignment. The result of periodically evaluating the studied scenarios indicates a relatively high accuracy. The accuracy of prediction in possible scenarios derived from the Basel Committee is 95.5% and in scenarios derived from experts' opinions, 75%. Manuscript profile
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  4 - A Framework for Sentiment Analysis in Social Networks based on Interpreting Contents
  Maryam Tayfeh-Mahmoudi َAmirmansour  Yadegari Parvin Ahmadi kambiz badie
  Interpreting contents with the aim of analyzing the sentiment of their narrators in social networks, holds a high significance due to the role of a content in disseminating information to the corresponding human groups. In this paper, we propose a framework for analyzin More

  Interpreting contents with the aim of analyzing the sentiment of their narrators in social networks, holds a high significance due to the role of a content in disseminating information to the corresponding human groups. In this paper, we propose a framework for analyzing sentiment on complex contents in a social network according to which a set of if-then type rules defined at high abstraction level, would be able to classify the messages behind these contents. According to this framework, items such as prosodic, context and key propositions are considered in the condition part of a rule and possible classes of message are taken into account in a rule’s action part. It is to be noted that the rules proposed for interpreting a content do not depend on the considered language due to the very inherent property of the items which are considered in interpretation. Results of experiments on a wide range of different contents in a social network support the fact that the proposed framework is sufficiently capable of analyzing the sentiments of contents’ narrators. Manuscript profile