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  • Open Access


    Deep Sentiment Learning for Measuring Similarity Recommendations in Twitter Data

    S. Manikandan1,*, P. Dhanalakshmi2, K. C. Rajeswari3, A. Delphin Carolina Rani4

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.023469

    Abstract The similarity recommendation of twitter data is evaluated by using sentiment analysis method. In this paper, the deep learning processes such as classification, clustering and prediction are used to measure the data. Convolutional neural network is applied for analyzing multimedia contents which is received from various sources. Recurrent neural network is used for handling the natural language data. The content based recommendation system is proposed for selecting similarity index in twitter data using deep sentiment learning method. In this paper, sentiment analysis technique is used for finding similar images, contents, texts, etc. The content is… More >

  • Open Access


    AI-based Automated Extraction of Location-Oriented COVID-19 Sentiments

    Fahim K. Sufi1,*, Musleh Alsulami2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3631-3649, 2022, DOI:10.32604/cmc.2022.026272

    Abstract The coronavirus disease (COVID-19) pandemic has affected the lives of social media users in an unprecedented manner. They are constantly posting their satisfaction or dissatisfaction over the COVID-19 situation at their location of interest. Therefore, understanding location-oriented sentiments about this situation is of prime importance for political leaders, and strategic decision-makers. To this end, we present a new fully automated algorithm based on artificial intelligence (AI), for extraction of location-oriented public sentiments on the COVID-19 situation. We designed the proposed system to obtain exhaustive knowledge and insights on social media feeds related to COVID-19 in 110… More >

  • Open Access


    Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

    Sami Ullah1, Muhammad Ramzan Talib1,*, Toqir A. Rana2,3, Muhammad Kashif Hanif1, Muhammad Awais4

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2323-2339, 2022, DOI:10.32604/cmc.2022.025543

    Abstract In the current era of the internet, people use online media for conversation, discussion, chatting, and other similar purposes. Analysis of such material where more than one person is involved has a spate challenge as compared to other text analysis tasks. There are several approaches to identify users’ emotions from the conversational text for the English language, however regional or low resource languages have been neglected. The Urdu language is one of them and despite being used by millions of users across the globe, with the best of our knowledge there exists no work on… More >

  • Open Access


    Stock Price Prediction Using Optimal Network Based Twitter Sentiment Analysis

    Singamaneni Kranthi Kumar1,*, Alhassan Alolo Abdul-Rasheed Akeji2, Tiruvedula Mithun3, M. Ambika4, L. Jabasheela5, Ranjan Walia6, U. Sakthi7

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1217-1227, 2022, DOI:10.32604/iasc.2022.024311

    Abstract In recent times, stock price prediction helps to determine the future stock prices of any financial exchange. Accurate forecasting of stock prices can result in huge profits to the investors. The prediction of stock market is a tedious process which involves different factors such as politics, economic growth, interest rate, etc. The recent development of social networking sites enables the investors to discuss the stock market details such as profit, future stock prices, etc. The proper identification of sentiments posted by the investors in social media can be utilized for predicting the upcoming stock prices.… More >

  • Open Access


    A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

    Muhammet Yasin PAK*, Serkan GUNAL

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1215-1239, 2022, DOI:10.32604/csse.2022.023051

    Abstract Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed model also reveals the difference between the concepts of opinion… More >

  • Open Access


    Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

    Shahid Mehmood1, Imran Ahmad1, Muhammad Adnan Khan1,2, Faheem Khan3, T. Whangbo3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5603-5618, 2022, DOI:10.32604/cmc.2022.023785

    Abstract Education sector has witnessed several changes in the recent past. These changes have forced private universities into fierce competition with each other to get more students enrolled. This competition has resulted in the adoption of marketing practices by private universities similar to commercial brands. To get competitive gain, universities must observe and examine the students’ feedback on their own social media sites along with the social media sites of their competitors. This study presents a novel framework which integrates numerous analytical approaches including statistical analysis, sentiment analysis, and text mining to accomplish a competitive analysis… More >

  • Open Access


    An Improved Method for Extractive Based Opinion Summarization Using Opinion Mining

    Surbhi Bhatia*, Mohammed AlOjail

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 779-794, 2022, DOI:10.32604/csse.2022.022579

    Abstract Opinion summarization recapitulates the opinions about a common topic automatically. The primary motive of summarization is to preserve the properties of the text and is shortened in a way with no loss in the semantics of the text. The need of automatic summarization efficiently resulted in increased interest among communities of Natural Language Processing and Text Mining. This paper emphasis on building an extractive summarization system combining the features of principal component analysis for dimensionality reduction and bidirectional Recurrent Neural Networks and Long Short-Term Memory (RNN-LSTM) deep learning model for short and exact synopsis using… More >

  • Open Access


    Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning

    Dhiaa A. Musleh, Taef A. Alkhales, Reem A. Almakki*, Shahad E. Alnajim, Shaden K. Almarshad, Rana S. Alhasaniah, Sumayh S. Aljameel, Abdullah A. Almuqhim

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3463-3477, 2022, DOI:10.32604/cmc.2022.022508

    Abstract Depression has been a major global concern for a long time, with the disease affecting aspects of many people's daily lives, such as their moods, eating habits, and social interactions. In Arabic culture, there is a lack of awareness regarding the importance of facing and curing mental health diseases. However, people all over the world, including Arab citizens, tend to express their feelings openly on social media, especially Twitter, as it is a platform designed to enable the expression of emotions through short texts, pictures, or videos. Users are inclined to treat their Twitter accounts… More >

  • Open Access


    Design of Automated Opinion Mining Model Using Optimized Fuzzy Neural Network

    Ala’ A. Eshmawi1, Hesham Alhumyani2, Sayed Abdel Khalek3, Rashid A. Saeed2, Mahmoud Ragab4, Romany F. Mansour5,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2543-2557, 2022, DOI:10.32604/cmc.2022.021833

    Abstract Sentiment analysis or Opinion Mining (OM) has gained significant interest among research communities and entrepreneurs in the recent years. Likewise, Machine Learning (ML) approaches is one of the interesting research domains that are highly helpful and are increasingly applied in several business domains. In this background, the current research paper focuses on the design of automated opinion mining model using Deer Hunting Optimization Algorithm (DHOA) with Fuzzy Neural Network (FNN) abbreviated as DHOA-FNN model. The proposed DHOA-FNN technique involves four different stages namely, preprocessing, feature extraction, classification, and parameter tuning. In addition to the above, More >

  • Open Access


    Course Evaluation Based on Deep Learning and SSA Hyperparameters Optimization

    Alaa A. El-Demerdash, Sherif E. Hussein, John FW Zaki*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 941-959, 2022, DOI:10.32604/cmc.2022.021839

    Abstract Sentiment analysis attracts the attention of Egyptian Decision-makers in the education sector. It offers a viable method to assess education quality services based on the students’ feedback as well as that provides an understanding of their needs. As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels, this research uses a dataset for tweets' sentiments to assess a few machine learning techniques. After dataset preprocessing to remove symbols, necessary stemming and lemmatization is performed for features extraction. This is followed by several machine learning techniques and… More >

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