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It is not uncommon to find the term "fake news" in social media platforms. While the former U.S. President Donald Trump accused the media of publishing fake news repeatedly during his term of office, many others saw the dissemination of false information as a big problem during the Brexit referendum. Given how social media accelerate the speed of information diffusion, the spread of misinformation has also become an unprecedented societal challenge in Hong Kong. Since the Anti-Extradition Law Amendment Bill Movement and the outbreak of COVID-19, the dissemination of disinformation has become an even greater concern. Mis/disinformation not only brings financial loss but also physical and psychological harm and even the possibility of tearing a society apart.

In fact, media practitioners and academic scholars have long been discussing the issue of misinformation, which nevertheless focuses on misinformation producers as well as ways to reduce the spread of misinformation, for instance, how authenticity can be ensured when delivering messages from the perspective of an organization or media outlet. Nonetheless, discussion focusing on the message receiver is seldom researched as extensively, such as how Hong Kong residents interpret the term "fake news" and the motivations that drive news users to accuse a piece of information as "fake news".

To understand how social media users apply the term "fake news", the Hong Kong Facebook News Analytics Dashboard ("the Dashboard") presents data of the Facebook public pages of 17 news outlets in Hong Kong from January 2019 to June 2021, including the text in posts, text in comments, and Uniform Resource Locator (URL) links, in addition to user engagement counts, such as frequencies of likes, shares, and post reactions.

Apart from the basic data, the Dashboard also provides opportunities to analyze the frequencies of "mentions of fake news" together with post themes, illustrated in dynamic visualization graphics. Dashboard users can search for news posts published in a specific time period, extract posts categorized under specific themes, and generate a list of news posts alongside their respective user engagement data. More importantly, users will obtain the number of "mentions of fake news" the posts obtained. In other words, the Dashboard allows the retrieval of data as well as the relationships among different data points.

In general, users can search for news posts by keywords, media types, and/or post themes. The Dashboard will generate a list of respective "User Reactions" (i.e., user engagement counts) and the frequency of "Mentions of fake news" (i.e., how many times the Facebook users mentioned the term "fake news" when they commented on the news posts). "User Reactions" include the numbers of likes, shares, and post reactions, whereas "Mentions of fake news" include the frequency of users mentioning the terms "fake news", "disinformation", and "rumors".

While this project is fully funded by the Digital Scholarship Grant, HKBU Library (Project No. DSG201902), the Dashboard is also part of a research project funded by the UGC General Research Fund, Hong Kong SAR (Project No. 1-73126).