An Application of the ELM Model to Information Sharing on Twitter: Studying the Role of Message Form and Sender Profile

This paper focuses on the information sharing behaviour of users within a micro-blogging platform, Twitter. We propose an explanatory model of the performance of a message by taking into account the external cues (source and form of the message) beyond the content and meaning of the text, and we test it empirically, on a corpus of nearly 800,000 original tweets sent by about 235,000 users over a period of 7 months concerning the Covid-19 epidemic in France. We thus show the importance of the source's credibility and its strategy on the platform, but also of the form of the post, its composition and its degree of elaboration. These elements are nuanced by the level of engagement of the source in the topic of conversation on which it intervenes and by the context in which these messages are sent and received. © 2022 Authors. All rights reserved.

The covid-19 crisis: An nlp exploration of the french twitter feed (february-may 2020)

The Covid-19 pandemic offers a spectacular case of disaster management. In this literature, the paradigm of participation is fundamental: the mitigation of the impact of the disaster, the quality of the preparation and the resilience of the society, which facilitate the reconstruction, depend on the participation of the populations. Being able to observe and measure the state of mental health of the population (anx-iety, confidence, expectations, …) and to identify the points of controversy and the content of the discourse, are necessary to support measures designed to encourage this participation. Social media, and in particular Twitter, offer valuable resources for researching this discourse. The objective of this empirical study is to reconstruct a micro history of users’ reactions to the pandemic as they share them on social networks. The general method used comes from new processing techniques derived from Natural Language Processing (NLP). Three analysis methods are used to process the corpus: analysis of the temporal evolution of term occurrences;creation of dynamic semantic maps to identify co-occurrences;analysis of topics using the SVM method. The main empirical result is that the mask emerges as a central figure of discourse, at least in the discourse produced by certain social media. The retrospective analysis of the phenomenon allows us to explain what made the mask a focal point not only in conversation, but also in behaviors. Its value resides less in its functional qualities than in its ability to fix attention and organize living conditions under the threat of pandemic. © Springer Nature Switzerland AG 2021.