The scientific work of members of our Department was published in the Economics and Business Review journal. The article “Artificial intelligence – friend or foe in fake news campaigns” focuses on analyzing the impact of large language models (LLM) on the phenomenon of fake news. On the one hand decent text‐generation capabilities can be misused for mass fake news production. On the other, LLMs trained on huge volumes of text … Read More
Artificial intelligence in fake news campaigns: experiments with ChatGPT
First place in the international competition CLEF-2023 CheckThat! Lab
The OpenFact project team took part in the CheckThat! organized as part of the international conference CLEF 2023 (Conference and Labs of the Evaluation Forum). The method proposed by our scientists took first place. This method detects English sentences that need to be reviewed because of potential misleading and therefore are worth fact-checking.
Companies in Multilingual Wikipedia: Articles Quality and Important Sources of Information
The scientific work of members of our Department was published in the monograph “Information Technology for Management: Approaches to Improving Business and Society” published by the Springer. The research concerns the automatic assessment of the quality of Wikipedia articles and the reliability of sources of information about companies in different languages.
Real or fake news? How not to get scammed on the Internet
During the 26th Poznań Science and Art Festival, members of our Department conducted a lecture on recognizing false information on the Internet. Participants had the opportunity to ask questions and share their experiences, which further enriched the discussion and made the event not only educational, but also interactive.
Presentation at Wiki Workshop 2023
On May 11, the tenth edition of the scientific forum for people studying various aspects of Wikipedia and other Wikimedia projects – Wiki Workshop 2023 took place. As part of this event, the results of scientific research in the area of analysis of global interest in American topics in the multilingual Wikipedia were presented.
Lectures and workshops during the ENIGMA Metropolitan Science Festival
Members of the Department of Information Systems conducted lectures and workshops during the five editions of the ENIGMA Metropolitan Science Festival. Over 1,000 students from various schools in Poznań and Szamotuły took part in the events. The materials presented during the Festival included issues related to the scientific research of our Department in the field of automatic identification of fake news on the Internet, assessment of the quality of information … Read More
Presentation at the conference “Bibliometric analyses of Open Science”
The highest score for the OpenFact project
The OpenFact project is run by the team of our Department in cooperation with technological and substantive partners, including: Google, Facebook, Bright Data, Harvard University, as well as leading fact-checking organizations in Poland. During the evaluation of the first phase of the INFOSTRATEG program of the National Center for Research and Development, in the field of fake news detection using artificial intelligence, the OpenFact project received the highest number of … Read More
Cryptocurrency market: evaluation of the effectiveness of strategies based on the RSI
Scientific article on effectiveness of the Relative Strength Index (RSI) signals in timing the cryptocurrency market was published in the “Sensors” journal. The journal’s Impact Factor for 2021 was 3.847, the five-year Impact Factor was 4.050. Authors of the publication: Marek Zatwarnicki, Krzysztof Zatwarnicki, Piotr Stolarski.
Important sources of information in different topics and language versions of Wikipedia
The scientific paper on automatic identification of important information sources on a specific topic in the multilingual Wikipedia based on analysis of more than 230 million references has been published on the Elsevier website. The study presents various models for automatic evaluation of information sources, which take into account the frequency of the information sources, the popularity of the content from readers and Wikipedia editors point of view.