• Title/Summary/Keyword: fact-checking

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News Article Identification Methods with Fact-Checking Guideline on Artificial Intelligence & Bigdata

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Advanced Culture Technology
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    • v.9 no.3
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    • pp.352-359
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    • 2021
  • The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

Information Verification Practices and Perception of Social Media Users on Fact-Checking Services

  • Rabby Q., Lavilles;January F., Naga;Mia Amor C., Tinam-isan;Julieto E., Perez;Eddie Bouy B., Palad
    • Journal of Information Science Theory and Practice
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    • v.11 no.1
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    • pp.1-13
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    • 2023
  • This study determines how social media users (SMUs) verify the information they come across on the Internet. It determines SMUs' perception of online fact-checking services in terms of their ease of use, usefulness, and trust. By conducting a focus group discussion and key informant interviews, themes were derived in determining fact-checking practices while a survey was further conducted to determine such perceived ease of use, usefulness, and trust in fact-checking services. The thematic analysis revealed major information verification practices, such as cross-checking and verifying with other sources, inspecting comments and reactions, and confirming from personal and social networks. The results showed that SMUs considered fact-checking services easy to use. However, a concern was raised about their usefulness stemming from the delayed action in addressing the information issues that need to be verified. As to perceived trust, it was found that SMUs have reservations about fact-checking services. Finally, it is believed that fact-checking services are expected to be credible and need to be promoted to mitigate any form of fake news, particularly on social media platforms.

Explainable Fact Checking Model Based on Efficient Transformer (효율적인 트랜스포머에 기반한 설명 가능한 팩트체크 모델)

  • Yun, Heeseung;Jung, Jason J.;Lee, Gunju;Jung, Dahee;Kim, Kono
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.19-21
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    • 2021
  • In this paper, we introduce the model so-called Explainable Fact-Checking model based on attention mechanism which shows both the result of fact check of the news and the evidence of verdict. Recently, several news surge on media, so fact check attracts much attentions. However, in present fact check relies on the search made by journalists and members of fact check orgainzation, so there is some researchs about automated fact checking. Therefore in this paper we propose explainable automated fact checking model.

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A Comparative Analysis of Fact-Checking News Fairness in South Korean Broadcasting (한국 방송의 팩트 체크 뉴스 공정성 비교 분석)

  • Dong, seho;Ahn, horim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.495-508
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    • 2023
  • To compare whether broadcast fact-checking news, which aims to overcome the limitations of objective reporting, ensures fairness, we analyzed 227 fact-checked news stories aired on the main news of KBS, MBC SBS, TV Chosun, JTBC MBN, and YTN from January 1, 2022 to May 31, 2022, when the 20th presidential and local election campaigns were held. The analysis showed clear differences in fact-checking targets and narratives by broadcasters. In general, MBC, JTBC,and YTN were more likely to favor liberal parties such as the Democratic Party, while TV Chosun had a lot of narratives favoring the conservative camp. SBS and MBN were relatively neutral. KBS seemed to be trying to remain outwardly neutral. SBS and TV Chosun were the most active in fact-checking, but they covered a wide range of issues and were characterized by a bias toward contextualizing issues that viewers were curious about, rather than clarifying the facts. The projection of ideological bias by broadcasters in fact-checking narratives is a challenge that needs to be overcome.

Automated Fact Checking Model Using Efficient Transfomer (효율적인 트랜스포머를 이용한 팩트체크 자동화 모델)

  • Yun, Hee Seung;Jung, Jason J.
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1275-1278
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    • 2021
  • Nowadays, fake news from newspapers and social media is a serious issue in news credibility. Some of machine learning methods (such as LSTM, logistic regression, and Transformer) has been applied for fact checking. In this paper, we present Transformer-based fact checking model which improves computational efficiency. Locality Sensitive Hashing (LSH) is employed to efficiently compute attention value so that it can reduce the computation time. With LSH, model can group semantically similar words, and compute attention value within the group. The performance of proposed model is 75% for accuracy, 42.9% and 75% for Fl micro score and F1 macro score, respectively.

An Analysis of the Fake News Assessment Criteria on Fact-check Coverage (팩트체크 보도의 가짜뉴스 판단 기준 검토)

  • Baek, Kanghui
    • The Journal of the Korea Contents Association
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    • v.20 no.2
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    • pp.172-181
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    • 2020
  • This study examines the fact-check coverage provided by the SNU fact-check center site(factcheck.snu.ac.kr). A total of 50 articles that were cross-checked by multiple news media organizations were analyzed. The study's variables were topics, types, characteristics, consistency of the news media organizations' judgement, and fact-check sources. This study found that fact-checking coverage was generally focused on presidential or general election candidates or politicians, as well as political topics. The types of fact-checking coverage primarily included factual information, as well as some opinions or interpretations. Fact-check coverage was mainly focused on the facts of the statements themselves, causal relationships, or the timing or target of the comparison criteria. On average, the fact-checking coverage most frequently assigned the judgment 'mostly false, and primarily used interviews of individuals or data from organizations involved in the issue, government data, and experts' statements as the bases for its fact-checking judgements.

Development of Drowsiness Checking System for Drivers using Eyes Image Histogram (눈 영상의 히스토그램을 이용한 운전자의 졸음 상태 체크 시스템 개발)

  • Kang, Su Min;Huh, Kyung Moo;Yang, Yeon Mo
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.4
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    • pp.330-335
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    • 2015
  • Approximately 23% of traffic accidents appear to be caused by drowsiness while driving. This fact shows that drowsy driving is a big factor in many traffic accidents. Therefore, the development of a drowsiness checking system is necessary to prevent drowsy driving. In this paper, we analyse the changes of the histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness checking system using this histogram change information. The experimental results show that our proposed method enhances the accuracy of checking drowsiness by nearly 98%, and can be used to prevent vehicle accidents due to the drowsiness of a driver.

Analyzing Patterns in News Reporters' Information Seeking Behavior on the Web (기자직의 웹 정보탐색행위 패턴 분석)

  • Kwon, Hye-Jin;Jeong, Dong-Youl
    • Journal of the Korean Society for information Management
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    • v.27 no.4
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    • pp.109-130
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    • 2010
  • The purpose of this study is to identify th patterns in the news reporters' information seeking behaviors by observing their web activities. For this purpose, transaction logs collected from 23 news reporters were analyzed. Web tracking software was installed to collect the data from their PCs, and a total of 39,860 web logs were collected in two weeks. Start and end pattern of sessions, transitional pattern by step, sequence rule model was analyzed and the pattern of Internet use was compared with the general public. the analysis of pattern derived a web information seeking behavior modes that consists of four types of behaviors: fact-checking browsing, fact-checking search, investigative browsing and investigative search.

A Study on Fake News Subject Matter, Presentation Elements, Tools of Detection, and Social Media Platforms in India

  • Kanozia, Rubal;Arya, Ritu;Singh, Satwinder;Narula, Sumit;Ganghariya, Garima
    • Asian Journal for Public Opinion Research
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    • v.9 no.1
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    • pp.48-82
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    • 2021
  • This research article attempts to understand the current situation of fake news on social media in India. The study focused on four characteristics of fake news based on four research questions: subject matter, presentation elements of fake news, debunking tool(s) or technique(s) used, and the social media site on which the fake news story was shared. A systematic sampling method was used to select a sample of 90 debunked fake news stories from two Indian fact-checking websites, Alt News and Factly, from December 2019 to February 2020. A content analysis of the four characteristics of fake news stories was carefully analyzed, classified, coded, and presented. The results show that most of the fake news stories were related to politics in India. The majority of the fake news was shared via a video with text in which narrative was changed to mislead users. For the largest number of debunked fake news stories, information from official or primary sources, such as reports, data, statements, announcements, or updates were used to debunk false claims.

Unraveling the Web of Health Misinformation: Exploring the Characteristics, Emotions, and Motivations of Misinformation During the COVID-19 Pandemic

  • Vinit Yadav;Yukti Dhadwal;Rubal Kanozia;Shri Ram Pandey;Ashok Kumar
    • Asian Journal for Public Opinion Research
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    • v.12 no.1
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    • pp.53-74
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    • 2024
  • The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.