Review
Chemistry, Multidisciplinary
Yili Wang, Jiaxuan Guo, Chengsheng Yuan, Baozhu Li
Summary: Twitter Sentiment Analysis is an active subfield of text mining, which has attracted considerable interest among researchers. This research provides a comprehensive review of the latest developments in this area, including newly proposed algorithms and applications. The survey classifies each publication based on its significance to specific TSA methods and depicts the current research direction in the field of TSA.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Sergiu Cosmin Nistor, Mircea Moca, Darie Moldovan, Delia Beatrice Oprean, Razvan Liviu Nistor
Summary: This paper introduces a sentiment analysis solution on tweets using Recurrent Neural Networks, achieving an accuracy rate of 80.74% after experimenting with 20 design approaches. The solution integrates an attention mechanism and a two-way localization system, based on an in-depth literature review for Twitter sentiment analysis.
Article
Computer Science, Artificial Intelligence
Maryum Bibi, Wajid Arshad Abbasi, Wajid Aziz, Sundus Khalil, Mueen Uddin, Celestine Iwendi, Thippa Reddy Gadekallu
Summary: Concept-based sentiment analysis (CBSA) methods have gained attention in natural language processing. These methods consider semantic meanings to analyze sentiment, but require supervised learning for better performance. To address the labeling issue, an unsupervised learning framework based on concept and hierarchical clustering is proposed, showing comparable performance with supervised learning techniques.
PATTERN RECOGNITION LETTERS
(2022)
Article
Computer Science, Software Engineering
Sajjad Haider, Muhammad Tanvir Afzal, Muhammad Asif, Hermann Maurer, Awais Ahmad, Abdelrahman Abuarqoub
Summary: The study examines the impact of different forms of adverbs on sentiment analysis, analyzing eight forms in total. The findings indicate that certain forms of adverbs play crucial roles in different types of opinions, with some being important for neutral opinions, positive opinions, and negative opinions.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Chemistry, Multidisciplinary
Naw Safrin Sattar, Shaikh Arifuzzaman
Summary: This study examines public attitudes towards COVID-19 vaccination and sentiment analysis on social media, showing that people have positive sentiments towards vaccination. Furthermore, post-vaccination, individuals are also positive about maintaining COVID-19 safety measures.
APPLIED SCIENCES-BASEL
(2021)
Article
Multidisciplinary Sciences
Ha-Linh Quach, Thai Quang Pham, Ngoc-Anh Hoang, Dinh Cong Phung, Viet-Cuong Nguyen, Son Hong Le, Thanh Cong Le, Thu Minh Thi Bui, Dang Hai Le, Anh Duc Dang, Duong Nhu Tran, Nghia Duy Ngu, Florian Vogt, Cong-Khanh Nguyen
Summary: This study examines the characteristics and trends of online information during a major COVID-19 outbreak in Da Nang province, Vietnam in July-August 2020. The findings show a close association between online information and the evolution of the COVID-19 situation. Online engagement increased during the outbreak and sentiment polarity varied depending on the topic. The study provides important insights about public awareness and perception during different outbreak phases.
Article
Computer Science, Artificial Intelligence
Despoina Antonakaki, Paraskevi Fragopoulou, Sotiris Ioannidis
Summary: Twitter is the third most popular online social network globally, with a simple data model and a straightforward data access API, making it ideal for social network studies. Research mainly focuses on the structure and properties of the social graph, sentiment analysis, and threats such as spam, bots, fake news, and hate speech.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Despoina Antonakaki, Paraskevi Fragopoulou, Sotiris Ioannidis
Summary: Twitter is a popular platform for research in social network studies, focusing on topics like social graph structure, sentiment analysis, and online threats. This survey provides insights into Twitter's data model, best practices, and computational techniques used in these areas, aiming to guide researchers in expanding on these topics.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Transportation Science & Technology
Yue Ding, Rostyslav Korolov, William (Al) Wallace, Xiaokun (Cara) Wang
Summary: The study analyzes sentiment changes towards autonomous vehicles (AVs) through social media tweets, revealing a general positive attitude towards AVs but also biases towards different AV terms. Significant sentiment changes are often associated with major social events, with the general public being more sensitive to these events.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Review
Computer Science, Artificial Intelligence
Quratulain Alvi, Syed Farooq Ali, Sheikh Bilal Ahmed, Nadeem Ahmad Khan, Mazhar Javed, Haitham Nobanee
Summary: Election prediction using sentiment analysis is a growing field that utilizes natural language processing and machine learning to predict election outcomes based on analyzing online conversations and news articles' sentiment. It can gauge public opinion and predict likely winners of elections.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Information Systems
Lanxue Dang, Chunyu Wang, Ming-Hsiang Tsou, Yan-e Hou, Hongyu Han
Summary: Social distancing is an important measure to prevent the spread of COVID-19. This study analyzed tweets from five English-speaking countries and found that the public generally has a positive attitude towards social distancing. Additionally, public sentiment fluctuates with changes in the daily number of new cases.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Panote Siriaraya, Yihong Zhang, Yukiko Kawai, Peter Jeszenszky, Adam Jatowt
Summary: This paper demonstrates how data from Open Street Map and Twitter can be used to analyze and depict fine-grained human emotions at a city-wide level in San Francisco and London. Through the development of neural network classifiers, emotions are detected from tweets and matched to key locations in Open Street Map. The analysis of the resulting data set reveals the impact of different days, locations, and POI neighborhoods on human emotion expression in the cities.
Article
Computer Science, Information Systems
Saleh Albahli, Aun Irtaza, Tahira Nazir, Awais Mehmood, Ali Alkhalifah, Waleed Albattah
Summary: This paper proposes a method to predict the future behavior of stock markets by analyzing Twitter posts and Google Finance data using an extended sentiment lexicon and machine learning algorithms. The experiments demonstrate that the method outperforms existing approaches in terms of accuracy. Future research plans to enhance the predictive capability by incorporating other social media platforms.
Article
Geosciences, Multidisciplinary
Ayse Cicek Korkmaz
Summary: This study conducts sentiment analysis on Twitter posts regarding society's perception of nursing education during the COVID-19 pandemic, shedding light on concerns, sentiments, and experiences related to nursing education during the crisis. The analysis reveals that nursing, education, health, school, and nurses are the most discussed keywords. 84% of the tweets express positive sentiments, 12% express negative sentiments, and 4% express neutral sentiments. The findings emphasize the importance of recognizing and appreciating the contributions of nurses and nursing students during the pandemic and addressing issues in nursing education to support more nursing professionals.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Medicine, General & Internal
Chayakrit Krittanawong, Hafeez Ul Hassan Virk, Craig L. Katz, Scott Kaplin, Zhen Wang, Joseph Gonzalez-Heydrich, Eric A. Storch, Carl J. Lavie
Summary: This study examined the positive effects of social gaming and social media on mental health during the COVID-19 pandemic, highlighting their importance in coping with stress.
AMERICAN JOURNAL OF MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Aleena Ahmad, Usman Qamar, Muhammad Summair Raza
APPLIED SOFT COMPUTING
(2020)
Article
Computer Science, Artificial Intelligence
Faryal Nosheen, Usman Qamar, Muhammad Summair Raza
Summary: Classical Rough Set Theory (RST) is a widely-used tool for dealing with uncertainty in categorical data, but it does not consider preference order of attribute values. Dominance-based Rough Set Approach (DRSA) is a generalization of RST that focuses on dominance aspect of attributes. The proposed heuristic approach for computing DRSA approximations shows a significant reduction in execution time and structural complexity, avoiding redundant computations and improving efficiency.
Proceedings Paper
Telecommunications
Usman Ali, Usman Qamar, Kanwal Wahab, Khawaj Sarmad Arif
ADVANCES IN INTERNET, DATA AND WEB TECHNOLOGIES (EIDWT 2020)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Younas Khan, Usman Qamar, Muhammad Asad, Babar Zeb
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Aiman Qadeer, Usman Qamar
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Muhammad Asad, Younas Khan, Usman Qamar, Saba Bashir
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 2
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Muhammad Asad, Usman Qamar
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 2
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Javeria Almas, Usman Qamar
2020 5TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA 2020)
(2020)
Proceedings Paper
Computer Science, Software Engineering
Iffat Fatima, Hina Anwar, Dietmar Pfahl, Usman Qamar
ICSOFT: PROCEEDINGS OF THE 15TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGIES
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Pakizah Saqib, Usman Qamar, Reda Ayesha Khan, Andleeb Aslam
2020 22ND INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): DIGITAL SECURITY GLOBAL AGENDA FOR SAFE SOCIETY!
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Aleena Ahmad, Usman Qamar, Summair Raza
2020 22ND INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): DIGITAL SECURITY GLOBAL AGENDA FOR SAFE SOCIETY!
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Andleeb Aslam, Usman Qamar, Pakizah Saqib, Reda Ayesha, Aiman Qadeer
2020 22ND INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): DIGITAL SECURITY GLOBAL AGENDA FOR SAFE SOCIETY!
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Andleeb Aslam, Usman Qamar, Reda Ayesha Khan, Pakizah Saqib
2020 22ND INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): DIGITAL SECURITY GLOBAL AGENDA FOR SAFE SOCIETY!
(2020)
Proceedings Paper
Computer Science, Information Systems
Anam Amjad, Usman Qamar
PROCEEDINGS OF THE 6TH CONFERENCE ON THE ENGINEERING OF COMPUTER BASED SYSTEMS (ECBS 2019)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Rabia Noureen, Usman Qamar, Farhan Hassan Khan, Iqra Muhammad
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1
(2019)