Detection of Fake News on COVID-19 on Web Search Engines
نویسندگان
چکیده
In early January 2020, after China reported the first cases of new coronavirus (SARS-CoV-2) in city Wuhan, unreliable and not fully accurate information has started spreading faster than virus itself. Alongside this pandemic, people have experienced a parallel infodemic, i.e., an overabundance information, some which is misleading or even harmful, widely spread around globe. Although social media are increasingly being used as source, web search engines, such Google Yahoo!, still represent powerful trustworthy resource for finding on Web. This due to their capability capture largest amount helping users quickly identify most relevant, useful, although always reliable, results queries. study aims detect potential fake contents by capturing analysing textual flow through engines. By using real-world dataset associated with recent COVID-19 we apply re-sampling techniques class imbalance, then use existing machine learning algorithms classification reliable news. extracting lexical host-based features uniform locators (URLs) news articles, show that proposed methods, so common phishing malicious URL detection, can improve efficiency performance classifiers. Based these findings, suggest both effectiveness detection methods.
منابع مشابه
On the Instability of Web Search Engines
The output of major WWW search engines was analyzed and the results led to some surprising observations about their stability. Twentyfive queries were issued repeatedly to the engines and the results were compared. After one month, the top ten results returned by eight out of nine engines had changed by more than fifty percent. Furthermore, five out of the nine engines returned over a third of ...
متن کاملAutomatic Detection of Fake News
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
متن کاملSexual Information Seeking on Web Search Engines
Sexual information seeking is an important element within human information behavior. Seeking sexually related information on the Internet takes many forms and channels, including chat rooms discussions, accessing Websites or searching Web search engines for sexual materials. The study of sexual Web queries provides insight into sexually-related information-seeking behavior, of value to Web use...
متن کاملDefining a session on Web search engines
Web searcher is an important area of research for designing more helpful searching systems and targeting content to particular users. Methods explored by other researchers include both qualitative (i.e., the use of human judges to manually analyze query patterns on usually small samples) and nondeterministic algorithms, typically using large amounts of training data to predict query modificatio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Physics
سال: 2021
ISSN: ['2296-424X']
DOI: https://doi.org/10.3389/fphy.2021.685730