Fake news detection has gained increasing importance among the research community due to the widespread diffusion of fake news through media platforms. Many dataset have been released in the last few years, aiming to assess the performance of fake news detection methods. In this survey, we systematically review twenty-seven popular datasets for fake news detection by providing insights into the characteristics of each dataset and comparative analysis among them. A fake news detection datasets characterization composed of eleven characteristics extracted from the surveyed datasets is provided, along with a set of requirements for comparing and building new datasets. Due to the ongoing interest in this research topic, the results of the analysis are valuable to many researchers to guide the selection or definition of suitable datasets for evaluating their fake news detection methods.

Local food traditions are an essential part of culture and society, reflecting a community’s history, values, and beliefs. Elders play a major role in passing on local food knowledge to younger generations, ensuring local food traditions and cultural identity do not disappear over time. To preserve these traditions, it is essential to engage older and younger generations of a community in a transgenerational dialogue. From this perspective, the study utilizes a hybrid participatory approach, composed of design thinking and learning-by-doing. Results of the case study underline the effectiveness of the approach in stimulating both the transfer of knowledge, as well as the involvement of younger generations, in the preservation of local food traditions.

This paper presents a new multimodal grammar generation system (MGGS) that allows defining a multimodal grammar in a very easy and intuitive way, overcoming the difficulties arising from the textual description of grammar production rules. The novelty of the proposed approach relies in adopting a “by example” paradigm to define a multimodal grammar. This paradigm consists in providing concrete examples of multimodal sentences, and enabling a grammar inference algorithm to automatically generate the grammar rules to parse those sentences. The main contribution of this approach is that it is general enough to be applicable for whatever modalities and in whichever domains. Moreover, the use of the grammar inference algorithm for automating the grammar writing and updating processes, reduces costs of the grammar development and maintenance. In the first part of this paper, we present the MGGS, describing in detail the methodology we have implemented in this system. More specifically, the multimodal attribute grammar and the grammar inference algorithm are illustrated. The second part describes the experiment aimed at observing participants while interacting with the system in order to provide some real data about the usability of the system. Results of this experiment showed that the proposed system facilitates the grammar definition and updating, and it is more suitable also for nonexpert people as it does not require the learning of the grammar notation.

The increasing need to access information everywhere and at any time leads us to believe that future user interfaces, through which users interact with pervasive computing systems, must address both device and modality independence. The pervasive computing paradigm sees almost every object in the everyday environment as a system able to communicate with users and other systems in their own languages. The interaction between users and systems is therefore typically multimodal. The main challenge of multimodal interaction, that is also the main topic of this paper, lies in developing a framework that is able to process information derived from whatever input modalities, giving these inputs an appropriate representation and integrating these individual representations into a joint semantic interpretation. A description of this multimodal pervasive framework will be given in this paper, along with some details of its application in Ambient Assisted Living and the usability test that was implemented to validate its effectiveness.