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Journal articles on the topic 'Opinion or Sentiment Mining'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Datt, Jivat Singh. "SENTIMENT ANALYSIS USING CUSTOMER FEEDBACK." International Journal of Trendy Research in Engineering and Technology 07, no. 04 (2023): 09–13. http://dx.doi.org/10.54473/ijtret.2023.7402.

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This Sentiment analysis is one of the fastest spreading research areas in computer science, making it challenging to keep track of all the activities in the area. We present customer feedback reviews on products, where we utilize opinion mining, text mining and sentiments, which has affected the surrounded world by changing their opinion on a specific product. Data used in this study are online product reviews collected from Amazon.com. We performed a comparative sentiment analysis of retrieved reviews. This research paper provides you with sentimental analysis of various smart phone opinions

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Kumar, Ravindra. "Methods to Perform Opinion Mining and Sentiment Analysis to Detect Factors Affecting Mental Health." International Journal of Engineering and Advanced Technology 11, no. 1 (2021): 70–72. http://dx.doi.org/10.35940/ijeat.f3025.1011121.

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Sentimental analysis and opinion extraction are emerging fields at AI. These approaches help organizations to use the opinions, sentiments, and subjectivity of their consumers in decision-making. Sentiments, views, and opinions show the feeling of the consumers towards a given product or service. In recent years, Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health. It’s Also true that human biasness is available in giving opinions, but it can be eliminated through the use of algorithms to get better results. However, it is crucial to

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Ravindra, Kumar. "Methods to Perform Opinion Mining and Sentiment Analysis to Detect Factors Affecting Mental Health." International Journal of Engineering and Advanced Technology (IJEAT) 11, no. 1 (2021): 70–72. https://doi.org/10.35940/ijeat.F3025.1011121.

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Sentimental analysis and opinion extraction are emerging fields at AI. These approaches help organizations to use the opinions, sentiments, and subjectivity of their consumers in decision-making. Sentiments, views, and opinions show the feeling of the consumers towards a given product or service. In recent years, Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health. It’s Also true that human biasness is available in giving opinions, but it can be eliminated through the use of algorithms to get better results. However, it is cruc

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Ms., Kalyani D. Gaikwad* Prof. Sonawane V.R. "OPINION MINING AND SENTIMENT ANALYSIS TECHNIQUES: A RECENT SURVEY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 12 (2016): 1003–6. https://doi.org/10.5281/zenodo.225397.

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Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service. The difficulties of performing sentiment analysis in this domain can be overcome by leveraging on common-sense knowledge bases. Opinion Mining is an area of text classification which continuously gives its contribution in research field. The main o

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Ramandeep, Sandhu, and Jyoti Kiran. "A NEW METHOD TO FIND SCORE VALUE FOR ONLINE OPINIONS." International Journal of Computational Science and Information Technology (IJCSITY) 1, February (2013): 1–9. https://doi.org/10.5281/zenodo.3631132.

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<strong>ABSTRACT </strong> In today’s world, we need information, not data to take a decision about a product. Opinions are data and become information after filtering. Also organizations products superiority is dependent on customer feedback of their products. Web is a platform providing facilities to post opinions for any product. A customer gives feedback when he uses a product and feedback is what customer feels after using it called sentiments/opinions. Opinions are subjective sentences and not objective as facts. People uses natural language to express sentiments and way of express

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Purohit, Amit. "Sentiment Analysis of Customer Product Reviews using deep Learning and Compare with other Machine Learning Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 233–39. http://dx.doi.org/10.22214/ijraset.2021.36202.

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Sentiment analysis is defined as the process of mining of data, view, review or sentence to Predict the emotion of the sentence through natural language processing (NLP) or Machine Learning Techniques. The sentiment analysis involve classification of text into three phase “Positive”, “Negative” or “Neutral”. The process of finding user Opinion about the topic or Product or problem is called as opinion mining. Analyzing the emotions from the extracted Opinions are defined as Sentiment Analysis. The goal of opinion mining and Sentiment Analysis is to make computer able to recognize and express e

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Bhardwaj, Shubham. "AN INDEPTH ANALYSIS OF CATEGORIZED MINING ALGORITHMS FOR OPINION MINING." International Journal of Research in Science and Technology 10, no. 01 (2022): 53–57. http://dx.doi.org/10.37648/ijrst.v10i01.011.

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Today's information and ideas can't be shared without social media. A person's day-to-day life is significantly affected by their emotional impact. An ecosystem that generates millions of bytes of data daily makes sentiment analysis essential for interpreting these enormous amounts of data. Sentiment analysis, a type of text mining, finds and extracts personal information from various sources, allowing businesses to monitor social sentiment about their brand, product, or service. Simply put, sentiment analysis enables one to ascertain the author's perspective on a topic. Writing is categorized

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Abubakar, B. U., and C. Uppin. "A NATURAL LANGUAGE PROCESSING APPROACH TO DETERMINE THE POLARITY AND SUBJECTIVITY OF IPHONE 12 TWITTER FEEDS USING TEXTBLOB." Open Journal of Physical Science (ISSN: 2734-2123) 2, no. 2 (2021): 10–17. http://dx.doi.org/10.52417/ojps.v2i2.276.

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Sentiment analysis and opinion mining is a branch of computer science that has gained considerable growth over the last decade. This branch of computer science deals with determining the emotions, opinions, feelings amongst others of a person on a particular topic. Social media has become an outlet for people to voice out their thoughts and opinions publicly about various topics of discussion making it a great domain to apply sentiment analysis and opinion mining. Sentiment analysis and opinion mining employ Natural Language Processing (NLP) in order to fairly obtain the mood of a person’s opi

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Miss, Komal, Devendra Kumar Vashist Er., and Balram Bhardwaj Er. "A NAIVE-BAYES STRATEGY FOR SENTIMENT ANALYSIS FOR E –CURRIER : FAST AND ACCURATE SENTIMENT CLASSIFICATION." International Journal of Advances in Engineering & Scientific Research 3, no. 2 (2024): 44–58. https://doi.org/10.5281/zenodo.10750567.

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<strong>Abstract: </strong>   <em>The amount of data readily available is far beyond our capacity to analyse and understand. The internet revolution has added to this problem by having billions of customer’s review data in its repositories. This has provoked an interest in sentiment analysis and opinion mining in the recent years. Opinion Mining is a process of automatic extraction of knowledge by means of opinion of others about some particular product, topic or problem. The idea of Opinion mining and Sentiment Analysis tool is to process a set of search results for a given item ba

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Vishwakarma, Shweta. "A Review Paper on Sentiment Analysis using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 11 (2023): 528–31. http://dx.doi.org/10.22214/ijraset.2023.56545.

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Abstract: Opinion Mining (OM) or Sentiment Analysis (SA) can be described as the process of identifying, extracting, and categorizing viewpoints on various subjects. It falls under the domain of natural language processing (NLP) and is commonly employed to gauge public sentiment towards specific laws, policies, marketing campaigns, and more. This involves the development of methodologies to collect and analyze comments and opinions posted on social media platforms concerning legislation, regulations, and other related matters. Information extraction plays a pivotal role in this process, as it

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Mannar Mannan, J., and Jayavel J. "An adaptive sentimental analysis using ontology for retail market." International Journal of Engineering & Technology 7, no. 1.2 (2017): 176. http://dx.doi.org/10.14419/ijet.v7i1.2.10666.

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The growth of digital documents on web becomes the massive sources for online market analyzing at broad level. The study of market research over online incorporating new parameter called sentiment analysis. The sentiment analysis plays a crucial role for identifying behavior of customers by means of natural language processing from customer feedback about product or services. The opinion mining have done from the user data over web related activities such as search history, blog activities, forums, comments on the social network, express the opinion about the concept/product and suggestion or

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Mannan, J. Mannar, and Jayavel .J. "An adaptive sentimental analysis using ontology for retail market." International Journal of Engineering & Technology 7, no. 1.3 (2017): 176. http://dx.doi.org/10.14419/ijet.v7i1.3.10676.

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The growth of digital documents on web becomes the massive sources for online market analyzing at broad level. The study of market research over online incorporating new parameter called sentiment analysis. The sentiment analysis plays a crucial role for identifying behavior of customers by means of natural language processing from customer feedback about product or services. The opinion mining have done from the user data over web related activities such as search history, blog activities, forums, comments on the social network, express the opinion about the concept/product and suggestion or

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Dua, Saurabh, Ishita Sharma, Shaurya Singh, and Kavishankar L. "Study of Different Algorithms on Opinion Mining." International Journal for Research in Applied Science and Engineering Technology 10, no. 9 (2022): 656–60. http://dx.doi.org/10.22214/ijraset.2022.46694.

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Abstract: Social media is critical in today's world for exchanging information and disseminating ideas. A person's emotional impact has a significant impact on their day-to-day life. Sentiment analysis is a form of text mining that locates and pulls out subjective information from sources, allowing a company to track discussions online and monitor social sentiment about their brand, product, or service. Simply put, sentiment analysis helps determine the author's attitude towards a topic. Positive, neutral, or negative pieces of writing are classified by sentiment analysis software. Deep learni

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Cristescu, Marian Pompiliu, Raluca Andreea Nerişanu, and Dumitru Alexandru Mara. "Using Data Mining in the Sentiment Analysis Process on the Financial Market." Journal of Social and Economic Statistics 11, no. 1-2 (2022): 36–58. http://dx.doi.org/10.2478/jses-2022-0003.

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Abstract Sentiment analysis refers to the analysis of human opinions and sentiments that are expressed in written text, being also a part of the Natural Language Processing (NLP) tasks. Sentiment analysis can be applied in different domains, especially in the corporate marketing and sales, the healthcare system or the financial market analysis. In this paper we aim to highlight how data mining is able to extract the sentiment score from a financial platform that shows the major headlines regarding stocks, in order to highlight the publications’ positive or negative opinion over a stock. In ord

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Tran, Trang Uyen, Ha Thanh Thi Hoan, Phuong Hoai Dang, and Michel Riveill. "Toward a multitask aspect-based sentiment analysis model using deep learning." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (2022): 516. http://dx.doi.org/10.11591/ijai.v11.i2.pp516-524.

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Sentiment analysis or opinion mining is used to understand the community’s opinions on a particular product. This is a system of selection and classification of opinions on sentences or documents. At a more detailed level, aspect-based sentiment analysis makes an effort to extract and categorize sentiments on aspects of entities in opinion text. In this paper, we propose a novel supervised learning approach using deep learning techniques for a multitasking aspect-based opinion mining system that supports four main subtasks: extract opinion target, classify aspect, classify entity (category) an

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Trang, Uyen Tran, Thanh Thi Hoang Ha, Hoai Dang Phuong, and Riveill Michel. "Toward a multitask aspect-based sentiment analysis model using deep learning." International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (2022): 516–24. https://doi.org/10.11591/ijai.v11.i2.pp516-524.

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Sentiment analysis or opinion mining is used to understand the community’s opinions on a particular product. This is a system of selection and classification of opinions on sentences or documents. At a more detailed level, aspect-based sentiment analysis makes an effort to extract and categorize sentiments on aspects of entities in opinion text. In this paper, we propose a novel supervised learning approach using deep learning techniques for a multitasking aspect-based opinion mining system that supports four main subtasks: extract opinion target, classify aspect, classify entity (catego

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Purba, Mariana, and Yadi Yadi. "Implementation Opinion Mining For Extraction Of Opinion Learning In University." SinkrOn 8, no. 2 (2023): 694–99. http://dx.doi.org/10.33395/sinkron.v8i2.11994.

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Opinion mining is a field of Natural Language Processing (NLP) that is used to carry out the process of extracting and processing textual data which functions to obtain information through sentiment analysis from a document in the form of text, among others, to detect attitudes towards objects or people. Sub-processes in opinion mining can use documents of subjectivity, opinion orientation, and detection targets to find out the data used as sentiment analysis, sentiment analysis aims to assess emotions, attitudes, opinions, and evaluations conveyed by a speaker or writer towards a product or t

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Bangkalang, Dwi Hosanna. "OPINION MINING OF REGIONAL HEADS IN INDONESIA USING THE SUPPORT VECTOR MACHINE (SVM) METHOD." JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 9, no. 3 (2024): 1622–27. http://dx.doi.org/10.29100/jipi.v9i3.5381.

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Social media is one of the communication mediums commonly used by regional heads to disseminate information, develop their image, and influence society through digital media. As a result, the regional head’s opinion on an issue is one of the factors that piques public interest in knowing where the opinions of regional heads lie. Opinion mining is the process of obtaining information or the analysis and summarization of opinions that are automatically voiced on particular topics or issues. A method is required to convert the regional leaders’ social media tweets into information and ideas that

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Dinesh M. "Smart Decisions with Opinion Mining." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 4 (2025): 466–71. https://doi.org/10.51583/ijltemas.2025.140400047.

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Abstract: The runaway growth of web technology has resulted in an unprecedented volume of data being produced and published on the web each day. Social networking sites such as Twitter and Facebook have turned into indispensable zones for individuals to share thoughts, experiences, and opinions around the world. Sentiment analysis which involves the extraction and analysis of opinion from text, is central to gauging public feeling, monitoring trends, business strategy, and customer satisfaction with regards to unstructured and heterogeneous nature of Twitter data, most research has been conduc

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Sharma, Abhishek. "An Enhanced Approach for Sentiment Analysis Using Association Rule Mining." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (2021): 913–18. http://dx.doi.org/10.22214/ijraset.2021.39404.

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Abstract: In today’s world social networking platforms like Facebook, YouTube, twitter etc. are a great source of communication for internet users and loaded with large number of emotions, views and opinions of the people. Sentiment analysis is the study of attitudes, emotions and opinions of the people and is also known as opinion mining. Sentiment analysis is used to find the opinion i.e. negative or positive about a particular subject. In this paper an Enhanced sentiment analysis approach is presented by using the Association rule mining i.e. Apriori and machine learning approach such as Su

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M.K., Sudha. "Social Media Sentiment Analysis for Opinion Mining." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 3672–79. http://dx.doi.org/10.37200/ijpr/v24i5/pr202075.

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Wijaya, Suryadi, and Yo Ceng Giap. "Twitter Opinion Mining Analysis of Web-Based Handphone Brand Using Naïve Bayes Classification Method." bit-Tech 4, no. 2 (2021): 56–60. http://dx.doi.org/10.32877/bt.v4i2.287.

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Social Media is now very commonly used for the benefit of society. People mostly use social media to convey information, give opinions, even for media to express themselves. One of the social media that is widely used to convey this information is Twitter. From the use of Twitter, a public opinion tweet emerged about a mobile phone product. The more that is posted on Twitter about cellphones, the more public opinion will arise about cellphone brands. From these opinions, a classification is needed that can distinguish Neutral, Negative, or Positive Opinions. Sentiment analysis or opinion minin

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Swati, Kunwar, and Bansla Neetu. "Opinion Mining Analysis: A Framework." Journal of Information Technology and Sciences 5, no. 3 (2019): 29–37. https://doi.org/10.5281/zenodo.3461312.

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<em>Opinion mining is a sort of natural language processing for tracing the emotional frame of mind of the public regarding a distinct or certain product. Opinion mining is otherwise called sentiment analysis as they are utilized reciprocally. The leading seriousness of sentiment analysis correlate with the leading of social media namely reviews blogs, Twitter and social network. Now, the consequence of all of this is that the physical analysis of such enormous or immense reviews is realistically or matter of factly beyond the bound of possibility. So, to answer this complication an automated

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B P Santosh Kumar. "An Intelligent Opinion Mining System with the Assistance of Bi-Directional Deep Recurrent Neural Network for Sentiment Analysis." Journal of Information Systems Engineering and Management 10, no. 12s (2025): 335–44. https://doi.org/10.52783/jisem.v10i12s.1815.

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Opinion mining, also referred to as sentiment analysis, has been an important research topic for identifying and analyzing opinions in natural language text. Computational linguistics and information retrieval are combined to extract and assess subjective information from textual data in this interdisciplinary field. In this work, I present a Bidirectional Deep Recurrent Neural Network (BDRNN) based framework for sentiment polarity detection. In this work, we propose the Sentiment Analysis using BDRNN (SA-BDRNN) system, which aims to overcome the challenges in extracting unbiased opinions from

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Kim, Tae Yeun, and Hyoung Ju Kim. "Opinion Mining-Based Term Extraction Sentiment Classification Modeling." Mobile Information Systems 2022 (April 27, 2022): 1–17. http://dx.doi.org/10.1155/2022/5593147.

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The spread of social media has accelerated the formation and dissemination of user review data, which contain subjective opinions of users on products, in an e-commerce environment. Because these reviews significantly influence other users, opinion mining has garnered substantial attention in analyzing the positive and negative opinions of users and deriving solutions based on these analytical results. Terms that include sentimental information and used in user reviews serve as the most crucial element in sentimental classification. In this regard, it is crucial to distinguish the most influen

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Karki, Sachit, and Arun Timalsina. "Opinion Mining of Customer Reviews for Online Products through Sentiment Analysis." Journal of Science and Technology 3, no. 1 (2023): 18–22. http://dx.doi.org/10.3126/jost.v3i1.69060.

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Sentiment essentially relates to feelings; attitudes, emotions and opinions. Sentiment Analysis refers to the practice of applying different Data Mining techniques to identify and extract subjective information from a piece of text. A person’s opinion or feelings are for the most part subjective and not facts, which means to accurately analyze an individual’s opinion or mood from a piece of text can be extremely difficult. Sentiment Analysis has gained much attention in recent years due to the importance of the automation in mining, extracting and processing information in order to analyze an

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Singh, Pradeep. "Near Real-time Sentiment Analysis using ChatGPT." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 706–9. http://dx.doi.org/10.22214/ijraset.2024.63216.

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Abstract: Sentiment analysis, also known as opinion mining, analyses people's opinions, sentiments, attitudes, and emotions from written language. With the rapid growth of social media and other real-time communication platforms, the demand for real-time sentiment analysis has surged. This paper explores the application of OpenAI's ChatGPT, a state-of-the-art language model, in conducting near real-time sentiment analysis. The study investigates the model's capabilities, performance, and potential limitations, proposing a framework for integrating ChatGPT into real-time sentiment analysis syst

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Kaur, Gaganpreet, Pratibha ., Amandeep Kaur, and Meenu Khurana. "A Review of Opinion Mining Techniques." ECS Transactions 107, no. 1 (2022): 10125–32. http://dx.doi.org/10.1149/10701.10125ecst.

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Opinion mining also known as Sentiment analysis is one of the most recent challenges in Natural Language Processing (NLP). Individuals expressing their opinions on various platforms such as Facebook, Twitter, and Yelp are also a difficult task because innovation has increased exponentially. With the popularity of social media, a massive amount of data namely comments, reviews and opinions have been generated. According to researchers, analysis of sentiments is based on a sentence level, document level, aspect level and user level. The analysis of this data consumes more time and is difficult f

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Terisri, Paladugula, Nandyala Hiranmayee, V. V. S. S. C. Ekantha S, Dungala Puthin, Kishor Ambati Karteek, and Tanmai Ramisetti Jyothi. "Sentimental Analysis using NLP." Sentimental Analysis using NLP 8, no. 12 (2023): 5. https://doi.org/10.5281/zenodo.10401483.

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Sentiment analysis is a subset of text analysis techniques that uses automatic text polarity detection. One of the main responsibilities of NLP (Natural Language Processing) is sentiment analysis, often known as opinion mining. In recent years, sentiment analysis has gained a lot of popularity. It is meant for people to build a system that can recognize and categorize sentiment or opinion as it is expressed in an electronic text. Nowadays, people who wish to purchase consumer goods prefer to read user reviews and participate in public online forums where others discuss the product. This is bec

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Aung, Sint Sint. "Analysis on Opinion Words Extraction in Electronic Product Reviews." International Journal of Systems and Software Security and Protection 10, no. 1 (2019): 47–61. http://dx.doi.org/10.4018/ijsssp.2019010103.

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Online user reviews are increasingly becoming important for measuring the quality of different products and services. Sentiment classification or opinion mining involves studying and building a system that collects data from online and examines the opinions. Sentiment classification is also defined as opinion extraction as the computational research area of subjective information towards different products. Opinion mining or sentiment classification has attracted in many research areas because of its usefulness in natural language processing and other area of applications. Extracting opinion w

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Pang, Bo, and Lillian Lee. "Opinion Mining and Sentiment Analysis." Foundations and Trends® in Information Retrieval 2, no. 1–2 (2008): 1–135. http://dx.doi.org/10.1561/1500000011.

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Liu, Bing. "Sentiment Analysis and Opinion Mining." Synthesis Lectures on Human Language Technologies 5, no. 1 (2012): 1–167. http://dx.doi.org/10.2200/s00416ed1v01y201204hlt016.

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Sasongko, Cornelius Damar, Rizal Isnanto, and Aris Puji Widodo. "Review of Systematic Literature about Sentiment Analysis Techniques." Jurnal Sistem Informasi Bisnis 15, no. 2 (2025): 227–36. https://doi.org/10.14710/vol15iss2pp227-236.

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Sentiment analysis, also known as opinion mining, is an important task in natural language processing and data mining. It involves extracting and analyzing subjective information from textual data to determine the sentiment or opinion expressed by the author. With the advancement of technology and the widespread use of social media and online review platforms, it is increasingly important to understand users' opinions and sentiments regarding a particular product, service or issue. The purpose of this research is to present a comprehensive literature review on sentiment analysis techniques. Th

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Bele, Nishikant, Prabin Kumar Panigrahi, and Shashi Kant Srivastava. "Political Sentiment Mining." International Journal of Business Intelligence Research 8, no. 1 (2017): 55–70. http://dx.doi.org/10.4018/ijbir.2017010104.

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Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English language cannot be applied directly to text in Hindi languages. The objective of this paper is to extract the political sentiment at the document-level from Hindi blogs. The authors could not find any literature about extracting sentiments at the document-level from Hindi blogs. They extracted opinion about one of India's very famous leaders who was a prominent face in the national election of 2014. They p

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Mauliza, Risha Nur, and Yoannes Romando Sipayung. "Penerapan Text Mining Dalam Menganalisis Pendapat Masyarakat Terhadap Pemilu 2024 Pada Media Sosial X Menggunakan Metode Naive Bayes." Technomedia Journal 9, no. 1 (2024): 1–16. http://dx.doi.org/10.33050/tmj.v9i1.2212.

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Tetx mining is a process to utilize the ocean of data in the Industrial Age 4.0. The rapid growth in the use of social media has generated a lot of data in the form of text analysis, one of which is sentiment analysis. This research uses social media X in analyzing the sentiment of opinions about the 2024 election. This analysis was taken from X social media user comments as much as 300 review data divided into 2 categories, namely 100 training data and 200 test data, then tested using the naïve bayes method. The text mining method with the naïve bayes algorithm can be applied to analyze publi

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P., Kavitha*1 &. Dr. M. Prabakaran2. "TWITTER SENTIMENT ANALYSIS BASED ON USER OPINION MINING USING MICROBLOG SUBSPACE ENSEMBLE CLASSIFICATION APPROACH IN SOCIAL WEB BLOG." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 8 (2018): 457–68. https://doi.org/10.5281/zenodo.1407450.

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Sentiment analysis rapidly used to manages content relation and variety of tweets terms from tweet comments which the comments are sentimental or opinion of the user. Online networking is producing a large measure of sentiment obtain from information as tweets, notices, blog posts and so forth. Sentiment analysis of this client produced realistic information is precious to identify the tweets texts of the group. Sentiment analysis from tremendous tweets is troublesomely contrasted with wide-ranging user thoughts, because of the closeness of words and different considerations create problem. Th

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Ardiansyah, Ricy, Herman Yuliansyah, and Anton Yudhana. "Multi-Label Classification for Opinion Mining in The Presidential Election using TF-IDF with NB And SVM." Jurnal ELTIKOM 9, no. 1 (2025): 35–46. https://doi.org/10.31961/eltikom.v9i1.1432.

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Public opinion plays a crucial role in presidential elections, shaping voter choices and influencing outcomes. Most sentiment analysis studies focus on binary (positive vs. negative) or multiclass (positive, negative, neutral) classification, which limits their ability to capture opinions that express multiple sentiments simultaneously. In presidential elections, a single opinion may support one candidate while criticizing another. This study proposes a MultiLabelBinarizer model to classify candidate and sentiment labels simultaneously—an approach that remains underexplored. The model combines

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Rahate, Samiksha, Vaishnavi Dehanka, Tanvi Teppalwar, and Vaishali R. Surjuse. "Review Sentimental Analysis." International Journal of Computer Science and Mobile Computing 11, no. 3 (2022): 37–41. http://dx.doi.org/10.47760/ijcsmc.2022.v11i03.005.

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Sentiment analysis or opinion mining is the computational study of people’s opinions, sentiments, attitudes, and emotions expressed in written language. It is one of the most active research areas in natural language processing and text mining in recent years. Its popularity is mainly due to two reasons. First, it has a wide range of applications because opinions are central to almost all human activities and are key influencers of our behaviors. Whenever we need to make a decision, we want to hear others’ opinions.

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Bahrawi, Nfn. "Sentiment Analysis Using Random Forest Algorithm-Online Social Media Based." Journal of Information Technology and Its Utilization 2, no. 2 (2019): 29. http://dx.doi.org/10.30818/jitu.2.2.2695.

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Every day billions of data in the form of text flood the internet be it sourced from forums, blogs, social media, or review sites. With the help of sentiment analysis, previously unstructured data can be transformed into more structured data and make this data important information. The data can describe opinions / sentiments from the public, about products, brands, community services, services, politics, or other topics. Sentiment analysis is one of the fields of Natural Language Processing (NLP) that builds systems for recognizing and extracting opinions in text form. At the most basic level

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J. Ibitoye, Ayodeji O., and Olufade F.W. Onifade. "Utilizing RoBERTa Model for Churn Prediction through Clustered Contextual Conversation Opinion Mining." International Journal of Intelligent Systems and Applications 15, no. 6 (2023): 1–8. http://dx.doi.org/10.5815/ijisa.2023.06.01.

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In computational study and automatic recognition of opinions in free texts, certain words in sentences are used to decide its sentiments. While analysing each customer’s opinion per time in churn management will be effective for personalised recommendations. Oftentimes, the opinion is not sufficient for contextualised content mining. While personalised recommendations are time consuming, it also does not provide complete picture of an overall sentiment in the business community of customers. To help businesses identify widespread issues affecting a large segment of their customers towards enge

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Chinedum, Amaechi, and Okeke Ogochukwu C. "A Review on Opinion Mining: Approaches, Practices and Application." International Journal on Recent and Innovation Trends in Computing and Communication 9, no. 3 (2021): 01–06. http://dx.doi.org/10.17762/ijritcc.v9i3.5456.

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Opinion Mining also known as Sentiment Analysis (SA) has recently become the focus of many researchers, because analysis of online text is useful and demanded in many different applications. Analysis of social sentiments is a trending topic in this era because users share their emotions in more suitable format with the help of micro blogging services like twitter. Twitter provides information about individual's real-time feelings through the data resources provided by persons. The essential task is to extract user's tweets and implement an analysis and survey. However, this extracted informati

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Hajmohammadi, Mohammad Sadegh, Roliana Ibrahim, and Zulaiha Ali Othman. "Opinion Mining and Sentiment Analysis: A Survey." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 3 (2012): 171–78. http://dx.doi.org/10.24297/ijct.v2i3c.2717.

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In the past few years, a great attention has been received by web documents as a new source of individual opinions and experience. This situation is producing increasing interest in methods for automatically extracting and analyzing individual opinion from web documents such as customer reviews, weblogs and comments on news. This increase was due to the easy accessibility of documents on the web, as well as the fact that all these were already machine-readable on gaining. At the same time, Machine Learning methods in Natural Language Processing (NLP) and Information Retrieval were considerably

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Nadiya Parveen,. "A Conceptual Framework for Leveraging Web Data in Sentiment Analysis and Opinion Mining." Journal of Information Systems Engineering and Management 10, no. 42s (2025): 562–70. https://doi.org/10.52783/jisem.v10i42s.7917.

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This paper introduces a comprehensive conceptual framework designed to enhance sentiment analysis and opinion mining by utilizing diverse web data sources. The framework integrates advanced computational techniques with innovative data harvesting methodologies to extract, process, and analyse sentiment data from various online platforms, including social media, forums, and blogs. At its core, the framework employs a hybrid model combining machine learning algorithms and natural language processing tools to accurately detect and interpret the sentiments and opinions embedded in unstructured web

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Al-Shukrawi, Ali Abbas Hadi, Layla Safwat Jamil, Israa Akram Alzuabidi, et al. "Opinion Mining in Arabic Extremism Texts: A Systematic Literature Review." AlKadhum Journal of Science 1, no. 2 (2023): 1–10. http://dx.doi.org/10.61710/akjs.v1i2.60.

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In this paper, a systematic literature review was provided that investigated the present evidence regarding extremist words in Arabic opinion mining methods. This study aimed to perform a Systematic Literature Review (SLR) in order to detect, evaluate, and synthesize the existing evidence regarding opinion mining techniques for extremist Arabic text. From the SLR, it is evident that opinion-mining techniques have several opportunities for detecting extremism in the Arabic text. Over the past few years, multimedia sentiment analysis has gained traction as visual content is becoming more incorpo

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Nethravathi, B., M. B. Apsara, G. Amitha, P. Bhuvana, and M. P. Akshatha. "Study of Techniques Used in Sentiment Analysis of Social Media Data." Journal of Information Technology and Sciences 5, no. 3 (2019): 21–28. https://doi.org/10.5281/zenodo.3379206.

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<em>With the advancement of internet, introduction of social media and exponential growth of the number of people actively participating in social media such as Facebook, Twitter and Instagram is increasing; there are lot of opinions expressed on social networking sites regarding various subjects. This data can be used in analysing the sentiments expressed pertaining to a particular subject matter which can be implemented. This can be used as the ideal research material for data scientists and researchers. This branch of data analytics known as sentiment analysis is used by companies to obtain

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Dwisyahputra, Achmad Adbillah, and Rakhmat Kurniawan. "Sentiment Analysis of Public Comments on Coldplay Concerts on Twitter Using the Naïve Bayes Method." Journal of Computer Networks, Architecture and High Performance Computing 6, no. 3 (2024): 1097–111. http://dx.doi.org/10.47709/cnahpc.v6i3.4202.

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Social media platform Twitter had become one of the most popular platforms for communication and information sharing. In the context of entertainment events such as music concerts, Twitter became a bustling place with various comments and opinions from the public regarding their experiences attending a concert. Many fans shared their experiences about Coldplay concerts on Twitter. These comments were highly varied and required a thorough understanding to interpret the overall public sentiment. Event organizers and Coldplay's band managers needed to understand public feelings about their concer

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Goswami, Mausumi, and Ahini Abraham. "Towards Sustainable Living through Sentiment Analysis during Covid19." ECS Transactions 107, no. 1 (2022): 18569–82. http://dx.doi.org/10.1149/10701.18569ecst.

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Artificial intelligence is the process of the machine to perform with the simulation of human intelligence. Computing within the field of emotions paves the recognitions to sentiment analysis. Sentiment analysis is the method of capturing the emotions behind a text whether or not it's positive, negative or neutral. Sentiment Analysis (SA) or Opinion Mining (OA) is the process to provide computational treatment to unstructured data to categorize and identify the sentiments or emotions expressed in a piece of text. It combines Natural Language Processing Techniques and Machine Learning Technique

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Sharma, Sristi, Dr Surendra Kumar Yadav, and Mr Lokendra Pal. "Opinion Mining Method for Sentiment Analysis." IOSR Journal of Computer Engineering 18, no. 05 (2016): 54–60. http://dx.doi.org/10.9790/0661-1805035460.

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Vanipriya, Ch, Thammi Reddy, and Pallavi R. "Sentiment Analysis-An opinion mining tool." International Journal Of Recent Advances in Engineering & Technology 08, no. 04 (2020): 33–37. http://dx.doi.org/10.46564/ijraet.2020.v08i04.008.

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Rana, Toqir A., Kiran Shahzadi, Tauseef Rana, Ahsan Arshad, and Mohammad Tubishat. "An Unsupervised Approach for Sentiment Analysis on Social Media Short Text Classification in Roman Urdu." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 2 (2022): 1–16. http://dx.doi.org/10.1145/3474119.

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During the last two decades, sentiment analysis, also known as opinion mining, has become one of the most explored research areas in Natural Language Processing (NLP) and data mining. Sentiment analysis focuses on the sentiments or opinions of consumers expressed over social media or different web sites. Due to exposure on the Internet, sentiment analysis has attracted vast numbers of researchers over the globe. A large amount of research has been conducted in English, Chinese, and other languages used worldwide. However, Roman Urdu has been neglected despite being the third most used language

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