Misinformation and Language Resources — LIRNEasia


LIRNEasia initiated its exploration of misinformation in 2018 following ethnic riots in Digana, Sri Lanka. The focus was on investigating automated rogue actors on social media, particularly through the analysis of tweets to comprehend their impact using data analytics. In 2020, the scope of our work expanded to encompass the examination of AI’s role in misinformation. This involved delving into the state of the art, designing, and testing over 400 machine learning models to assess algorithmic efficacy, data requirements, as well as hardware and liveware costs. The outcomes included the development of new misinformation datasets and models tailored for Sinhala and Bengali.

Leveraging our strengths in qualitative research, the team also probed into the challenges faced by regional fact checkers and journalists. We explored the practical aspects of technology adoption in this context through key informant interviews. In 2021, LIRNEasia conducted a scoping study funded by IDRC to comprehend the nature of information disorder and strategies to counteract it. The study output comprises a comprehensive map of actors and frameworks, an evaluation of current approaches and tools used by stakeholder groups, and an overview of the research landscape. The scoping study involved both desk research and key informant interviews.

Previous research by LIRNEasia delved into the nature of information disorder in Asia, mapping the involved actors and examining the actions and strategies employed. The findings highlighted that fact-checking, awareness campaigns, training programs (including digital literacy initiatives), and policy changes were among the widely adopted strategies to combat information disorder.

Currently, LIRNEasia is engaged in two projects related to information disorder. The first, titled “Human Factors in Information Disorder and Finding Measures to Counter: An Experimental Approach Leading to New Knowledge Creation,” is conducted in collaboration with Watchdog and Sarvodaya Fusion. Simultaneously, the second project addresses information disorder at the grassroots level, with training programs specifically designed for school children.


Documents

  • “Day of Information Disorder”: Evidence-Based Solutions for a Resilient Digital Age

    On July 3, 2025, in Colombo, LIRNEasia organized the “Day of Information Disorder” to disseminate research findings from two major studies: a nationally representative survey and an experimental study measuring the effectiveness of misinformation countering measures. The event brought together researchers, journalists, media professionals, tech innovators, and policy experts to address one of today’s most urgent challenges: information disorder. The day began with an introduction by Helani Galpaya, CEO of LIRNEasia, who set the tone by unpacking what information disorder is and why it matters. LIRNEasia researcher Shenali Bamaramannage followed with a thought-provoking presentation titled “Are we idiots?”, sharing key findings from LIRNEasia’s national research on the human factors influencing susceptibility to misinformation in Sri Lanka. Isuru Samaratunga, Research Manager at LIRNEasia, then addressed the question: “Are there solutions?” His presentation offered a comparative analysis of different interventions aimed at countering misinformation, laying the foundation for the discussions that followed. A lively panel discussion explored how to optimize limited resources toward solutions that truly work. The panel featured Nipunika Ruhunage (CEO, Sarvodaya Fusion), Rahul Namboori (CEO, Fact Crescendo), Kumar Lopez (CEO, Sri Lanka Press Institute), Deepanjalie Abeywardena (Deputy Director, Verité Research), and Samaratunga (Research Manager, LIRNEasia), moderated by Helani Galpaya […]

  • Launch of the Information Disorder Research in Sri Lanka and a Forum on Building Digital Resilience

    On the 1st of July 2025, LIRNEasia in collaboration with the University of Jaffna held an event titled Launch of the information disorder research in Sri Lanka and a forum on building digital resilience. The event centered around the launch of results from a LIRNEasia study assessing the ability of Tamil news readers in Sri Lanka to classify information as true/false, and measuring the effectiveness of popular countermeasures to misinformation, such as fact-checking and media literacy programs. The opening address was given by Prof. Sivakolundu Srisatkunarajah, Vice Chancellor of the University of Jaffna, talked about the digital revolution, the newer challenges arising due to the information disorder and the importance of information literacy as a counter measure. The chief guest at the event, the Hon. Governor of the Northern Province, Mr. Nagalingam Vethanayahan spoke next and pointed out that although the issue of misinformation has existed since ancient times, the digital era has significantly amplified its reach and impact, making it increasingly difficult to distinguish truth from falsehood.  He noted that the comprehensive study by LIRNEasia on this topic was groundbreaking. LIRNEasia researchers Sachini Ranasinghe presented the findings from the survey, which is representative of all Tamil news readers in […]

  • Tackling online misinformation while protecting freedom of expression (Event Report)

    An Expert Round Table discussion on “Tackling online misinformation while protecting freedom of expression” held on the 11th of October 2021, as the second of a series of discussions under the theme of “Frontiers of Digital Economy”

  • Webinar on Information Disorder

    LIRNEasia joined a webinar on Information Disorder organized by University of Cape Town on 6 May 2022. This event was based on the collaborative Global South report on Information Disorder where LIRNEasia authored the chapter on Asian region. 

  • Use of AI in classifying Misinformation [White Paper]

    A white paper exploring the use of AI in classifying misinformation. 

  • Misinformation in Bangladesh: A Brief Primer

    Over the past decade, both internet penetration and digital media user base have increased substantially.

  • A Corpus and Machine Learning Models for Fake News Classification in Bengali

    We present a dataset consisting of 3468 documents in Bengali, drawn from Bangladeshi news websites and factchecking operations, annotated as CREDIBLE, FALSE, PARTIAL or UN-CERTAIN. The dataset has markers for the content of the document, the classification, the web domain from which each document was retrieved, and the date on which the document was published. We also present the results of misinformation classification models built for the Bengali language, as well as comparisons to prior work in English and Sinhala.

  • A Corpus and Machine Learning Models for Fake News Classification in Sinhala

    We present a dataset consisting of 3576 documents in Sinhala, drawn from Sri Lankan news websites and factchecking operations, annotated as CREDIBLE, FALSE, PARTIAL or UN- CERTAIN. The dataset has markers for the content of the document, the classification, the web domain from which each document was retrieved, and the date on which the document was published. We also present the results of misinformation classification models built for the Sinhala language, as well as comparisons to English benchmarks, and suggest that for smaller media ecosystems it may make more practical sense to model uncertainty instead of truth vs falsehood binaries.

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