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Early Detection of Social Media Hoaxes at Scale [article]

Arkaitz Zubiaga, Aiqi Jiang
2020 arXiv   pre-print
The unmoderated nature of social media enables the diffusion of hoaxes, which in turn jeopardises the credibility of information gathered from social media platforms.  ...  Experiments using class-specific representations of word embeddings show that we can achieve F1 scores nearing 72% within 10 minutes of the first tweet being posted when we expand the size of the training  ...  in social media. • We perform experiments using class-specific representations of word embeddings for effective detection of hoaxes.  ... 
arXiv:1801.07311v3 fatcat:jl6plimnwjbufbhxf6gt5ebpzu

A Survey on Various Methods to Detect Rumors on Social Media

2020 Computer Engineering and Intelligent Systems  
A cutting edge portraying the utilization of directed ML algorithms for rumor detection via Social networking media is introduced.  ...  This paper is an introduction to rumor recognition via social networking media which presents the essential wording and kinds of bits of rumor and the nonexclusive procedure of rumor detection.  ...  In the proposed model, CNN is used to learn the hidden representations of specific tweets by extracting a sequence of high level phrase representations as input to LSTM, providing the tweet representation  ... 
doi:10.7176/ceis/11-4-01 fatcat:u5i7p4wz2nfxbbmvedmekjjwim

Hoax detection system on Indonesian news sites based on text classification using SVM and SGD

Agung B. Prasetijo, R. Rizal Isnanto, Dania Eridani, Yosua Alvin Adi Soetrisno, M. Arfan, Aghus Sofwan
2017 2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)  
An early detection on hoaxes helps the Government to reduce and even eliminate the spread.  ...  Each word in news articles can be modeled as feature and with Linear SVC and SGD, the feature of word vector can be reduced into two dimensions and can be separated using linear and non-linear lines.  ...  ACKNOWLEDGMENT This work was supported by The Ministry of Research, Technology and Higher Education, Republic of Indonesia.  ... 
doi:10.1109/icitacee.2017.8257673 fatcat:zerwgsb7wfhdjh4bouz27v27rq

Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter

Svitlana Volkova, Kyle Shaffer, Jin Yea Jang, Nathan Hodas
2017 Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)  
Fabricated stories in social media, ranging from deliberate propaganda to hoaxes and satire, contributes to this confusion in addition to having serious effects on global stability.  ...  Pew research polls report 62 percent of U.S. adults get news on social media (Gottfried and Shearer, 2016) .  ...  Department of Energy.  ... 
doi:10.18653/v1/p17-2102 dblp:conf/acl/VolkovaSJH17 fatcat:qsq3slif2jcjraxxobbrbx5cym

An Emotional Analysis of False Information in Social Media and News Articles

Bilal Ghanem, Paolo Rosso, Francisco Rangel
2020 ACM Transactions on Internet Technology  
social media and online news articles sources.  ...  In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from  ...  ACKNOWLEDGMENTS The work of the second author was partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKEnews and  ... 
doi:10.1145/3381750 fatcat:kfh2ztoq65ghfjihqjj6mcnrgu

An Emotional Analysis of False Information in Social Media and News Articles [article]

Bilal Ghanem, Paolo Rosso, Francisco Rangel
2019 arXiv   pre-print
social media and online news articles sources.  ...  In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from  ...  To the best of our knowledge, this is the first work that analyzes the impact of emotions in the detection of false information considering both social media and news articles.  ... 
arXiv:1908.09951v1 fatcat:ib3darz7qzdwzcq3lpysmbhxta

Rumor Detection on Social Media: Datasets, Methods and Opportunities [article]

Quanzhi Li, Qiong Zhang, Luo Si, Yingchi Liu
2019 arXiv   pre-print
Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques.  ...  Social media platforms have been used for information and news gathering, and they are very valuable in many applications. However, they also lead to the spreading of rumors and fake news.  ...  Rumor Early Detection Rumor early detection is to detect a rumor at its early stage before it wide-spreads on social media, so that one can take appropriate actions earlier.  ... 
arXiv:1911.07199v1 fatcat:h4fk3dyodjgyvffwuo6q5d2tnm

Motivations, Methods and Metrics of Misinformation Detection: An NLP Perspective

Qi Su, Mingyu Wan, Xiaoqian Liu, Chu-Ren Huang
2020 Natural Language Processing Research  
The past few decades have witnessed the critical role of misinformation detection in enhancing public trust and social stability.  ...  This paper discusses the main issues of misinformation and its detection with a comprehensive review on representative works in terms of detection methods, feature representations, evaluation metrics and  ...  ACKNOWLEDGMENTS We are grateful to the anonymous reviewers for their valuable and constructional advices on the previous versions of this article; all remaining errors are our own.  ... 
doi:10.2991/nlpr.d.200522.001 fatcat:vwwspvaexbga3kn5mxtdo6ke6u

Combating Fake News: A Survey on Identification and Mitigation Techniques [article]

Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
2019 arXiv   pre-print
The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion  ...  While much of the earlier research was focused on identification of fake news based on its contents or by exploiting users' engagements with the news on social media, there has been a rising interest in  ...  The views and conclusions are those of the authors and should not be interpreted as representing the social policies of the funding agency, or the U.S. Government.  ... 
arXiv:1901.06437v1 fatcat:xa2ecuhp4fcy5jetoiz5qchg6a

Case Study on Detecting COVID-19 Health-Related Misinformation in Social Media [article]

Mir Mehedi A. Pritom, Rosana Montanez Rodriguez, Asad Ali Khan, Sebastian A. Nugroho, Esra'a Alrashydah, Beatrice N. Ruiz, Anthony Rios
2021 arXiv   pre-print
This increase in social media usage has made it a prime vehicle for the spreading of misinformation.  ...  This paper presents a mechanism to detect COVID-19 health-related misinformation in social media following an interdisciplinary approach.  ...  This finding highlights the need for misinformation detection and content removal policies for social media.  ... 
arXiv:2106.06811v1 fatcat:3rstecrsdrdkbavrxx5ij2532q

Monitoring Cyber SentiHate Social Behavior during COVID-19 Pandemic in North America

Fatimah Alzamzami, Abdulmotaleb El Saddik
2021 IEEE Access  
[52] proposed using domain-specific word embedding with BERT model to detect white supremacist hate speech if it existed on social media.  ...  BERT models have shown state-of-the-art performance in detecting hate speech on social media [47] , [48] . Marzieh et al.  ... 
doi:10.1109/access.2021.3088410 fatcat:dl32i5vlovevvcokm6sbdp6ev4

A Survey on Computational Propaganda Detection [article]

Giovanni Da San Martino, Stefano Cresci, Alberto Barron-Cedeno, Seunghak Yu, Roberto Di Pietro, Preslav Nakov
2020 arXiv   pre-print
In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts  ...  They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach millions of social  ...  In other words, the focus shifted from feature engineering to learning effective feature representations and of designing brand-new and customized algorithms [Cai et al., 2017] .  ... 
arXiv:2007.08024v1 fatcat:i4xhy7tgvbc45mxrjif4apne2a

Reasoning About Inconsistent Formulas

Joao Marques-Silva, Carlos Mencía
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
problems, but also explainability of machine learning models.  ...  The analysis of inconsistent formulas finds an ever-increasing range of applications, that include axiom pinpointing in description logics, fault localization in software, model-based diagnosis, optimization  ...  In other words, the focus shifted from feature engineering to learning effective feature representations and of designing brand-new and customized algorithms [Cai et al., 2017] .  ... 
doi:10.24963/ijcai.2020/672 dblp:conf/ijcai/MartinoCBYPN20 fatcat:7fdnmougz5cllmi2no3qrd7wia

Rumor Detection in Social Media with User Information Protection

Md Rashed Ibn Nawab, Kazi Md. Shahiduzzaman, Titya Eng, Md. Noor Jamal
2020 European Journal of Electrical Engineering and Computer Science  
Many researchers have already shown that only user-based or content-based features are not enough to detect rumor in social media and for better prediction we need to consider both.  ...  In our research, we argue that the word embedding feature and sentiment score with subjectivity can also play a vital role in this detection task.  ...  detect rumor in social media?  ... 
doi:10.24018/ejece.2020.4.4.219 fatcat:m3x2uca5jrez7id4v2uw5awwxq

Clickbait Detection in YouTube Videos [article]

Ruchira Gothankar, Fabio Di Troia, Mark Stamp
2021 arXiv   pre-print
In effect, users are tricked into clicking on clickbait videos. In this research, we consider the challenging problem of detecting clickbait YouTube videos.  ...  We experiment with multiple state-of-the-art machine learning techniques using a variety of textual features.  ...  Their work focused on detecting clickbait posts in online social media.  ... 
arXiv:2107.12791v1 fatcat:tyzpwuvhxvcwlgutmsvqrzqspu
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