Article
Humanities, Multidisciplinary
Wen-zhong Shi, Fanxin Zeng, Anshu Zhang, Chengzhuo Tong, Xiaoqi Shen, Zhewei Liu, Zhicheng Shi
Summary: As COVID-19 spread globally, social media became an important channel for people to communicate and exchange information. This study analyzes the development of fine-grained emotions in online public opinion during the COVID-19 epidemic in China, revealing a high emotional effect during holidays and a sharp rise in fear especially in Wuhan and surrounding areas. The study also shows that central cities had stronger reactions to the epidemic compared to neighboring cities.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2022)
Article
Health Care Sciences & Services
Cathy Yan, Melanie Law, Stephanie Nguyen, Janelle Cheung, Jude Kong
Summary: This study used location-based subreddits on Reddit to study city-level sentiments towards vaccine-related topics, identifying 13 topics with a focus on vaccines. Joy was a predominant sentiment in the comments analyzed. The findings suggest that city-specific data from social media can provide valuable insights into local sentiments and concerns surrounding COVID-19 vaccines.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Review
Information Science & Library Science
Sanjeev Verma
Summary: This study provides a comprehensive analysis of sentiment analysis research articles and highlights its applications in market insights, innovation, transparency, citizen participation, and improved efficiency in public services. It also identifies its potential in addressing social problems and building smart societies.
GOVERNMENT INFORMATION QUARTERLY
(2022)
Article
Computer Science, Artificial Intelligence
Dingqi Yang, Bingqing Qu, Philippe Cudre-Mauroux
Summary: The article explores the unique characteristics of location-centric social media data, including spatial, temporal, semantic, and social dimensions, and emphasizes three key challenges in data analytics. It also discusses the opportunities of leveraging this data for urban analytics and smart city development, including data analysis within and across the four data dimensions.
IEEE INTELLIGENT SYSTEMS
(2021)
Article
Mathematics, Interdisciplinary Applications
M. G. Cosenza, O. Alvarez-Llamoza, C. Echeverria, K. Tucci
Summary: This study employs an agent-based model to investigate the impact of spatial heterogeneities on the collective behavior of a social system. The research finds that a high density of obstacles contributes to cultural diversity, while the distribution of opinion leaders promotes multiculturalism and serves as locations for the formation of boundaries and segregation between cultural groups. Additionally, a lower density of leaders than obstacles is needed to induce multiculturalism in the system.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Environmental Sciences
Mohammadsepehr Karimiziarani, Wanyun Shao, Majid Mirzaei, Hamid Moradkhani
Summary: There has been extensive research on the use of social media data during disasters, especially on platforms like Twitter. This study analyzed 35 million tweets during hurricanes Harvey and Dorian using Natural Language Processing techniques. The findings reveal valuable insights into social response to hurricanes and provide assistance to crisis management agencies and disaster responders.
CLIMATE RISK MANAGEMENT
(2023)
Article
Chemistry, Multidisciplinary
Yu-Ya Cheng, Yan-Ming Chen, Wen-Chao Yeh, Yung-Chun Chang
Summary: Private entrepreneurs and government organizations widely use Facebook fan pages to engage with the public and understand their emotional responses, with the help of a Bi-directional Long Short-Term Memory (BiLSTM) model proposed to efficiently predict sentiment information in social media text. This method can assist in improving the effectiveness of social media operations through the analysis of public opinions.
APPLIED SCIENCES-BASEL
(2021)
Article
Green & Sustainable Science & Technology
Nabila Mohamad Sham, Azlinah Mohamed
Summary: This study aimed to find the most effective sentiment analysis approach for climate change tweets and related domains. The results showed that the hybrid method outperformed other approaches, with the hybrid TextBlob and Logistic Regression achieving the highest F1-score of 75.3%. The study also found that lemmatization improved the accuracy of machine learning and hybrid approaches, while the TF-IDF feature extraction technique slightly outperformed Bag-of-Words.
Editorial Material
Computer Science, Theory & Methods
David Camacho, Ma Victoria Luzon, Erik Cambria
Summary: The rapid growth of social media platforms and their associated applications has revolutionized the way billions of people interact on the Web, driving innovations in user-centered applications and efficient data processing techniques. Recent advances in data science and artificial intelligence have made these developments possible, as evidenced by the 12 selected papers in this special issue representing the latest advances in fields like pattern recognition, information fusion, knowledge discovery, and data visualization.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Geosciences, Multidisciplinary
Faith Ka Shun Chan, Xinbing Gu, Yunfei Qi, Dimple Thadani, Yongqin David Chen, Xiaohui Lu, Lei Li, James Griffiths, Fangfang Zhu, Jianfeng Li, Wendy Y. Chen
Summary: This article discusses the lessons learned by Ningbo municipality from two strong typhoons, including the use of Big Data and Social Media to reduce flood impacts and the implementation of Flood Insurance to speed up recovery processes. Successful preparation, response, and recovery helped Ningbo enhance its flood resilience and reduce losses.
Article
Urban Studies
Tan Yigitcanlar, Nayomi Kankanamge, Karen Vella
Summary: Smart cities are a hot topic globally, with a study aiming to evaluate the perceptions and utilizations of smart city concepts and technologies in cities. The most popular smart city concepts are innovation, sustainability, and governance, while the most popular technologies are internet-of-things, artificial intelligence, and autonomous vehicle technology.
JOURNAL OF URBAN TECHNOLOGY
(2021)
Article
Multidisciplinary Sciences
Corrado Monti, Luca Maria Aiello, Gianmarco De Francisci Morales, Francesco Bonchi
Summary: This study investigates which messages are more effective at inducing a change of opinion in the listener within the frame of Habermas' theory of communicative action. By utilizing natural language processing, the researchers extract latent social dimensions of a message and identify key ingredients to opinion change, such as knowledge, similarity, and trust. The findings suggest that voicing conflict in a structured public debate can promote integration.
SCIENTIFIC REPORTS
(2022)
Review
Computer Science, Information Systems
Miguel A. Alonso, David Vilares, Carlos Gomez-Rodriguez, Jesus Vilares
Summary: Fake news has been on the rise in recent years, posing a serious threat to social cohesion and trust in leaders. Automatic systems for fake news detection have become increasingly important due to the unfeasibility of manual verification, with sentiment analysis playing a key role in this process.
Article
Environmental Sciences
Max Falkenberg, Alessandro Galeazzi, Maddalena Torricelli, Niccolo Di Marco, Francesca Larosa, Madalina Sas, Amin Mekacher, Warren Pearce, Fabiana Zollo, Walter Quattrociocchi, Andrea Baronchelli
Summary: This study examines the intersection of climate change and political polarization by analyzing Twitter data from the United Nations Conference of the Parties on Climate Change (COP) from 2014 to 2021. The findings reveal a significant increase in ideological polarization during COP26, driven by right-wing activity. Furthermore, a range of 'climate contrarian' views emerged during COP26, with the theme of political hypocrisy gaining cross-ideological appeal. These results highlight the importance of monitoring polarization and its impact on public climate discourse, especially considering future climate negotiations at COP27 and beyond.
NATURE CLIMATE CHANGE
(2022)
Article
Energy & Fuels
Dorota Walentek
Summary: Datafication plays a key role in the development of smart cities, and the use of social media is closely related to a city's performance in global smart city rankings. The study found that cities with higher social media usage tend to rank better, showcasing a direct correlation between digital engagement and urban success.
Article
Computer Science, Information Systems
Souad Hadjres, Nadjia Kara, May El Barachi, Fatna Belqasmi
Summary: This paper introduces a novel social gaming based approach for forming cloud coalitions, which aims to find the best coalition of cloud providers to respond to requests while meeting clients' SLA requirements. The proposed algorithm, S-ACCF, leverages Irving's roommate algorithm to quickly form stable coalitions, maximizing profit and minimizing the number of participants and penalties incurred by providers failing to offer promised resources. Extensive testing shows that S-ACCF outperforms existing approaches in terms of execution time, provider payoff, and coalition stability, making it suitable for production environments.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2021)
Article
Computer Science, Information Systems
May El Barachi, Faouzi Kamoun, Abderrazek Hachani, Fatna Belqasmi, Amir Ben Said, Imed Amri
Summary: This paper presents a location-based crowdsourcing solution for COPD patients to request emergency oxygen supply, utilizing a trusted platform to facilitate crowd responses. The approach involves geo-temporal data analysis and computer vision techniques, with a focus on human-centric computer interaction design.
PERSONAL AND UBIQUITOUS COMPUTING
(2021)
Article
Green & Sustainable Science & Technology
Payyazhi Jayashree, May El Barachi, Feras Hamza
Summary: Sustainability leadership aims to balance short-term economic goals with long-term sustainable development goals by considering the interests of all stakeholders. This study proposes a data-driven, multi-level, multi-stakeholder framework that demonstrates the dynamic interplay between micro, meso, and macro factors. The framework provides insights into the key factors impacting sustainability leadership in the context of SMEs operating in an emerging market.
Article
Green & Sustainable Science & Technology
Imene Ajala, Shanaz Feroze, May El Barachi, Farhad Oroumchian, Sujith Mathew, Rand Yasin, Saad Lutfi
Summary: Public opinion plays a crucial role in influencing policy changes and political strategies, with extreme public opinion having the potential to lead to radical behaviors and violent actions. Social media platforms are used for recruitment and radicalization, while data mining and natural language processing techniques are employed for detecting extremism and radicalization.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Information Systems
Ahmed Saleh Bataineh, Jamal Bentahar, Rabeb Mizouni, Omar Abdel Wahab, Gaith Rjoub, May El Barachi
Summary: This paper argues for reshaping the role of the cloud from a passive virtual market to an active platform for monetizing data. The objective is to enable data providers to reach a wider range of consumers and expose them to a greater variety of data for the benefit of data analytic applications. To achieve this, a novel game theoretical model is proposed, utilizing a mix of cooperative and competitive strategies, and taking into account network effects among the players. Simulations using Amazon and Google clustered data demonstrate that this model improves the total surplus of involved parties in terms of cloud resources provision and monetary profits compared to the current merchant model.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Article
Social Issues
Taghreed Abu Salim, May El Barachi, Ahmed Alfatih D. Mohamed, Susanne Halstead, Nasser Babreak
Summary: Blockchain, as a disruptive technology, promises to revolutionize trusted transactions by reducing costs, time, friction, and fraud, and ensuring trust and identity management in business dealings. The study found that the perceived cost does not mediate but moderates the relationship between organizational readiness and the intention to adopt blockchain technology, with the highest performance impact on the intention to adopt blockchain.
TECHNOLOGY IN SOCIETY
(2022)
Article
Social Issues
May El Barachi, Taghreed Abu Salim, Munyaradzi W. Nyadzayo, Sujith Mathew, Amgad Badewi, Joseph Amankwah-Amoah
Summary: This study examines the relationship between citizens' readiness and intention to continue usage of smart city services (SCS), and identifies the mediators of satisfaction and discomfort. The findings suggest that empowerment, optimism, and innovativeness enhance continuous usage when mediated by satisfaction, while discomfort mediates the negative impact of inhibitors. The study highlights the role of technology readiness and proposes a new scale and model for measuring users' readiness to adopt and continuously use SCS.
TECHNOLOGY IN SOCIETY
(2022)
Article
Computer Science, Information Systems
May El Barachi, Sujith Samuel Mathew, Farhad Oroumchian, Imene Ajala, Saad Lutfi, Rand Yasin
Summary: Future smart cities adopt a data-centric approach to decision-making, and public opinion monitoring is crucial for governments and intelligence agencies. However, existing approaches fail to capture the complexity of the radicalization process. This study proposes a sophisticated framework for analyzing the behavior of extremists on social media platforms, achieving promising results.
JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Mohammad M. Masud, Kadhim Hayawi, Sujith Samuel Mathew, Temesgen Michael, Mai El Barachi
Summary: Online exams are popular in online learning, but detecting cheating poses a challenge. To reduce cheating, educational institutes use online exam proctoring tools, with the most common technique being recording video and audio of the exam. However, manually analyzing these videos is impractical. This paper proposes a cheating detection technique that analyzes exam videos using deep learning and traditional machine learning models, achieving high prediction accuracy.
ADVANCED DATA MINING AND APPLICATIONS, ADMA 2021, PT I
(2022)
Article
Computer Science, Information Systems
Imran Makhdoom, Kadhim Hayawi, Mohammed Kaosar, Sujith Samuel Mathew, Pin-Han Ho
Summary: Collaborative Intrusion Detection Systems are effective in defending large Industrial Internet of Things against cyberattacks, but the threat of internal malicious attacks exists. This article proposes a device integrity check mechanism based on Digital Genome to detect compromised nodes in the network.
Proceedings Paper
Computer Science, Theory & Methods
Abdul Munem Nerabie, Manar AlKhatib, Sujith Samuel Mathew, May El Barachi, Farhad Oroumchian
Summary: Sentiment analysis, achieved through NLP techniques, plays a crucial role in analyzing social media content, but faces challenges in analyzing Arabic language, particularly with the addition of social media dialects.
12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Faouzi Kamoun, May El Barachi, Fatna Belqasmi, Abderrazak Hachani
Summary: The paper introduces a system that collects safety data through sensor nodes and guides evacuees in real time by considering the changing risks of each hallway segment, ensuring they move towards the appropriate exit direction.
12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS
(2021)
Article
Information Science & Library Science
Taghreed Abu Salim, May El Barachi, Okey Peter Onyia, Sujith Samuel Mathew
Summary: This study investigates the impact of Smart City Services delivery-channel characteristics and users' personal characteristics on user satisfaction and intention to continue using the services. Contrary to popular belief, it is found that not only SCS channel factors but also users' personal characteristics play a crucial role in determining user satisfaction and intention to continue using the SCS-delivery channels.
INFORMATION TECHNOLOGY & PEOPLE
(2021)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)