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Around 10% to 20% of patients experience Long COVID after recovering from COVID-19. Many people are turning to social networks such as Facebook, WhatsApp, Twitter, etc., to express their opinions and feelings regarding Long COVID. In this paper, we analyse text messages in the Greek language posted on the Twitter platform in 2022 to extract popular discussion topics and classify the sentiment of Greek citizens regarding Long COVID. Results highlighted the following discussion topics: Greek-speaking users discuss Long COVID effects and time required to heal, Long COVID effects in specific population groups like children and COVID-19 vaccines. 59% of analysed tweets conveyed a negative sentiment while the rest had positive or neutral sentiment. The analysis shows that public bodies could benefit from systematically mining knowledge from social media to understand public's perception of a new disease and take action.

In this article, a prototype Greek text to Greek Sign Language (GSL) conversion system is presented. The system is integrated into an educational platform that addresses the needs of teaching GSL grammar and was developed within the SYNENNOESE project (Efthimiou et al. 2004a. Developing an e-learning platform for the Greek sign language. In: K. Miesenberger, J. Klaus, and W. Zagler, eds. Computer helping people with special needs, Lecture Notes in Computer Science, Springer-Verlag, vol. 3118, 1107-1113). The detailed implementation of the language-processing component of a Greek text to GSL conversion system is provided, focusing upon the inherent problems of knowledge elicitation of sign language (SL) grammar and its implementation within a parser framework. It is based on an SL dictionary (Efthimiou et al. 2004a) database of coded GSL knowledge. The proposed system has been designed and implemented after considering most state-of-the-art SL machine translation or Conversion systems, such as Vsigns (Papadogiorgaki et al. 2004. VSigns - a virtual sign synthesis web tool. In: Proceedings of Sixth COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, May 2004, Thessaloniki, Greece), ZARDOZ (Veale et al. 1998. The challenges of cross-modal translation: English to sign language translation in the ZARDOZ system. Machine Translation, 13, 81-106) and SignSynth (Angus 2001. SignSynth: a sign language synthesis application using Web3D and Perl. In: Gesture and Sign Lanauage in Human-Computer Interaction. London, UK: International Gesture Workshop), and taking into account their advantages and disadvantages. The overall architecture is innovative since other existing systems either do not consider the GSL or they cannot be effectively applied on sentences but just on single words. The system is demonstrable on any conventional PC. [ABSTRACT FROM AUTHOR]