S. Saranya^*, G. Usha

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 339-352, 2023, DOI:10.32604/iasc.2023.031987 - 29 September 2022

Abstract Laterally with the birth of the Internet, the fast growth of mobile strategies has democratised content production owing to the widespread usage of social media, resulting in a detonation of short informal writings. Twitter is microblogging short text and social networking services, with posted millions of quick messages. Twitter analysis addresses the topic of interpreting users’ tweets in terms of ideas, interests, and views in a range of settings and fields. This type of study can be useful for a variation of academics and applications that need knowing people’s perspectives on a given topic or… More >

Sandeep Kumar¹, Muhammad Badruddin Khan², Mozaherul Hoque Abul Hasanat², Abdul Khader Jilani Saudagar^2,*, Abdullah AlTameem², Mohammed AlKhathami²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 897-914, 2023, DOI:10.32604/cmc.2023.031867 - 22 September 2022

Abstract Social media, like Twitter, is a data repository, and people exchange views on global issues like the COVID-19 pandemic. Social media has been shown to influence the low acceptance of vaccines. This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individual’s sensitivities and feelings that lead to achievement. This work proposes a method to analyze the opinion of an individual’s tweet about the COVID-19 vaccines. This paper introduces a sigmoidal particle swarm optimization (SPSO) algorithm. First, the performance of SPSO is measured on a set of 12 benchmark problems,… More >

C. P. Thamil Selvi^1,*, P. Muneeshwari², K. Selvasheela³, D. Prasanna⁴

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3545-3555, 2023, DOI:10.32604/iasc.2023.031097 - 17 August 2022

Abstract The term sentiment analysis deals with sentiment classification based on the review made by the user in a social network. The sentiment classification accuracy is evaluated using various selection methods, especially those that deal with algorithm selection. In this work, every sentiment received through user expressions is ranked in order to categorise sentiments as informative and non-informative. In order to do so, the work focus on Query Expansion Ranking (QER) algorithm that takes user text as input and process for sentiment analysis and finally produces the results as informative or non-informative. The challenge is to More >

C. P. Thamil Selvi^1,*, R. PushpaLakshmi²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2439-2456, 2023, DOI:10.32604/csse.2023.029254 - 01 August 2022

Abstract One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics. Bigdata is created from social websites like Facebook, WhatsApp, Twitter, etc. Opinions about products, persons, initiatives, political issues, research achievements, and entertainment are discussed on social websites. The unique data analytics method cannot be applied to various social websites since the data formats are different. Several approaches, techniques, and tools have been used for big data analytics, opinion mining, or sentiment analysis, but the accuracy is yet to be improved. The proposed work is motivated to do… More >

G. Indra^1,*, N. Duraipandian²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1455-1470, 2023, DOI:10.32604/iasc.2023.027703 - 19 July 2022

Abstract A flood is a significant damaging natural calamity that causes loss of life and property. Earlier work on the construction of flood prediction models intended to reduce risks, suggest policies, reduce mortality, and limit property damage caused by floods. The massive amount of data generated by social media platforms such as Twitter opens the door to flood analysis. Because of the real-time nature of Twitter data, some government agencies and authorities have used it to track natural catastrophe events in order to build a more rapid rescue strategy. However, due to the shorter duration of… More >

Ayman Mohamed Mostafa^*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1015-1034, 2023, DOI:10.32604/iasc.2023.028041 - 06 June 2022

Abstract Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects. Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy. The sentiment analysis accuracy depends mainly on supervised and unsupervised mechanisms. Supervised mechanisms are based on machine learning algorithms that achieve moderate or high accuracy but the manual annotation of data is considered a time-consuming process. In unsupervised mechanisms, a lexicon is constructed for storing polarity terms. The accuracy of analyzing data is considered moderate or low if the lexicon contains small terms. In addition,… More >

K. Sailaja Kumar^*, H. K. Manoj, D. Evangelin Geetha

Computer Systems Science and Engineering, Vol.44, No.1, pp. 485-499, 2023, DOI:10.32604/csse.2023.025390 - 01 June 2022

Abstract Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints. A parallel computational environment provided by Apache Hadoop can distribute and process the data over different destination systems. In this paper, the Hadoop cluster with four nodes integrated with RHadoop, Flume, and Hive is created to analyze the tweets gathered from the Twitter stream. Twitter stream data is collected relevant to an event/topic like IPL- 2015, cricket, Royal Challengers Bangalore, Kohli, Modi, from May 24 to 30, 2016 using Flume. Hive is used as a data warehouse to store the… More >

Ankur Dumka¹, Parag Verma², Rajesh Singh³, Anil Kumar Bisht⁴, Divya Anand^5,6,*, Hani Moaiteq Aljahdali⁷, Irene Delgado Noya^6,8, Silvia Aparicio Obregon^6,9

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6029-6044, 2022, DOI:10.32604/cmc.2022.024698 - 21 April 2022

Abstract Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this… More >

S. Manikandan^1,*, 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 - 15 April 2022

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 >

Singamaneni Kranthi Kumar^1,*, 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 - 08 February 2022

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 >