Adel Assiri¹, Abdu Gumaei^2,*, Faisal Mehmood^3,*, Touqeer Abbas⁴, Sami Ullah⁵

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4219-4236, 2024, DOI:10.32604/cmc.2024.050781

Abstract Modern technological advancements have made social media an essential component of daily life. Social media allow individuals to share thoughts, emotions, and ideas. Sentiment analysis plays the function of evaluating whether the sentiment of the text is positive, negative, neutral, or any other personal emotion to understand the sentiment context of the text. Sentiment analysis is essential in business and society because it impacts strategic decision-making. Sentiment analysis involves challenges due to lexical variation, an unlabeled dataset, and text distance correlations. The execution time increases due to the sequential processing of the sequence models. However,… More >

Zohaib Ahmad Khan¹, Yuanqing Xia^1,*, Ahmed Khan², Muhammad Sadiq², Mahmood Alam³, Fuad A. Awwad⁴, Emad A. A. Ismail⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2771-2793, 2024, DOI:10.32604/cmc.2024.046897

Abstract Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significant source of user-generated content. The development of sentiment lexicons that can support languages other than English is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existing sentiment analysis systems focus on English, leaving a significant research gap in other languages due to limited resources and tools. This research aims to address this gap by building a sentiment lexicon for local languages, which is then used with a machine learning algorithm for efficient sentiment analysis.… More >

S. Sofana Reka¹, Ankita Bagelikar², Prakash Venugopal^2,*, V. Ravi², Harimurugan Devarajan³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 781-794, 2024, DOI:10.32604/cmc.2023.043369

Abstract The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality, flavor and nutritional value. The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers. The impact of rotten fruits can foster harmful bacteria, molds and other microorganisms that can cause food poisoning and other illnesses to the consumers. The overall purpose of the study is to classify rotten fruits, which can affect the taste, texture, and appearance of other fresh fruits, thereby reducing their shelf life.… More >

Mian Muhammad Danyal¹, Sarwar Shah Khan^2,4, Muzammil Khan^2,*, Muhammad Bilal Ghaffar¹, Bilal Khan¹, Muhammad Arshad³

Journal on Big Data, Vol.5, pp. 1-18, 2023, DOI:10.32604/jbd.2023.041319

Abstract Movies are the better source of entertainment. Every year, a great percentage of movies are released. People comment on movies in the form of reviews after watching them. Since it is difficult to read all of the reviews for a movie, summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews. Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data. Opinion mining involves identifying and extracting the opinions of individuals, which can be positive, neutral, or negative. The… More >

Zhifang Liao¹, Hao Gu¹, Shichao Zhang¹, Ronghui Mo¹, Yan Zhang^2,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 599-618, 2023, DOI:10.32604/iasc.2023.036794

Abstract Context-Sensitive Task (CST) is a complex task type in crowdsourcing, such as handwriting recognition, route plan, and audio transcription. The current result inference algorithms can perform well in simple crowdsourcing tasks, but cannot obtain high-quality inference results for CSTs. The conventional method to solve CSTs is to divide a CST into multiple independent simple subtasks for crowdsourcing, but this method ignores the context correlation among subtasks and reduces the quality of result inference. To solve this problem, we propose a result inference algorithm based on the Partially ordered set and Tree augmented naive Bayes Infer… More >

Khalid M. O. Nahar^1,*, Mohammad Alauthman², Saud Yonbawi³, Ammar Almomani^4,5

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5307-5319, 2023, DOI:10.32604/cmc.2023.031848

Abstract Social media networks are becoming essential to our daily activities, and many issues are due to this great involvement in our lives. Cyberbullying is a social media network issue, a global crisis affecting the victims and society as a whole. It results from a misunderstanding regarding freedom of speech. In this work, we proposed a methodology for detecting such behaviors (bullying, harassment, and hate-related texts) using supervised machine learning algorithms (SVM, Naïve Bayes, Logistic regression, and random forest) and for predicting a topic associated with these text data using unsupervised natural language processing, such as More >

Joseph Bamidele Awotunde¹, Sanjay Misra^2,*, Vikash Katta², Oluwafemi Charles Adebayo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 131-154, 2023, DOI:10.32604/cmes.2023.026812

Abstract The task of classifying opinions conveyed in any form of text online is referred to as sentiment analysis. The emergence of social media usage and its spread has given room for sentiment analysis in our daily lives. Social media applications and websites have become the foremost spring of data recycled for reviews for sentimentality in various fields. Various subject matter can be encountered on social media platforms, such as movie product reviews, consumer opinions, and testimonies, among others, which can be used for sentiment analysis. The rapid uncovering of these web contents contains divergence of… More >

Kashif Saleem¹, Rashid Naseem¹, Khalil Khan^1,2, Siraj Muhammad³, Ikram Syed^4,*, Jaehyuk Choi^4,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3517-3533, 2023, DOI:10.32604/iasc.2023.036356

Abstract Automation software need to be continuously updated by addressing software bugs contained in their repositories. However, bugs have different levels of importance; hence, it is essential to prioritize bug reports based on their severity and importance. Manually managing the deluge of incoming bug reports faces time and resource constraints from the development team and delays the resolution of critical bugs. Therefore, bug report prioritization is vital. This study proposes a new model for bug prioritization based on average one dependence estimator; it prioritizes bug reports based on severity, which is determined by the number of More >

D. Palanikkumar¹, R. Ramesh Kumar², Mehedi Masud³, Mrim M. Alnfiai⁴, Mohamed Abouhawwash^5,6,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2425-2440, 2023, DOI:10.32604/iasc.2023.033879

Abstract The major environmental hazard in this pandemic is the unhygienic disposal of medical waste. Medical wastage is not properly managed it will become a hazard to the environment and humans. Managing medical wastage is a major issue in the city, municipalities in the aspects of the environment, and logistics. An efficient supply chain with edge computing technology is used in managing medical waste. The supply chain operations include processing of waste collection, transportation, and disposal of waste. Many research works have been applied to improve the management of wastage. The main issues in the existing… More >

Hameedur Rahman¹, Junaid Tariq^2,*, M. Ali Masood¹, Ahmad F. Subahi³, Osamah Ibrahim Khalaf⁴, Youseef Alotaibi⁵

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5527-5543, 2023, DOI:10.32604/cmc.2023.033190

Abstract Sentiment Analysis (SA) is often referred to as opinion mining. It is defined as the extraction, identification, or characterization of the sentiment from text. Generally, the sentiment of a textual document is classified into binary classes i.e., positive and negative. However, fine-grained classification provides a better insight into the sentiments. The downside is that fine-grained classification is more challenging as compared to binary. On the contrary, performance deteriorates significantly in the case of multi-class classification. In this study, pre-processing techniques and machine learning models for the multi-class classification of sentiments were explored. To augment the… More >