The present paper contributes to the research on the activities of farright actors on social media by examining the interconnections between far-right actors and groups on Telegram platform using network analysis. The far-right network observed on Telegram is highly decentralized, similarly to the far-right networks found on other social media platforms. The network is divided mostly along the ideological and national lines, with the communities related to 4chan imageboard and Donald Trump's supporters being the most influential. The analysis of the network evolution shows that the start of its explosive growth coincides in time with the mass bans of the far-right actors on mainstream social media platforms. The observed patterns of network evolution suggest that the simultaneous migration of these actors to Telegram has allowed them to swiftly recreate their connections and gain prominence in the network thus casting doubt on the effectiveness of deplatforming for curbing the influence of far-right and other extremist actors.

Online messaging app Telegram has increased in popularity in recent years surpassing Twitter and Snapchat by the number of active monthly users in late 2020. The messenger has also been crucial to protest movements in several countries in 2019-2020, including Belarus, Russia and Hong Kong. Yet, to date only few studies examined online activities on Telegram and none have analyzed the platform with regard to the protest mobilization. In the present study, we address the existing gap by examining Telegram-based activities related to the 2019 protests in Hong Kong. With this paper we aim to provide an example of methodological tools that can be used to study protest mobilization and coordination on Telegram. We also contribute to the research on computational text analysis in Cantonese—one of the low-resource Asian languages,—as well as to the scholarship on Hong Kong protests and research on social media-based protest mobilization in general. For that, we rely on the data collected through Telegram’s API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i.e., police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders—those prominent during the 2014 Umbrella Movement,—such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020. Further investigation is necessary to assess the persistence of this effect in a long-term perspective.

We examine Telegram-based activities related to the 2019 protests in Hong Kong thus presenting the first study of a large Telegram-aided protest movement. We contribute to both - scholarship on Hong Kongese protests and research on social media-based protest mobilization. For that, we rely on the data collected through Telegram’s API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring the efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i.e., police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders - those prominent during the 2014 Umbrella Movement, - such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020. Further investigation is necessary to assess the persistence of this effect in a long-term perspective.

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The aim of this chapter is to present a methodology for supporting the collaboration between the involved parties and for augmenting the final product with an always up to date digital file. The methodology is based on three support tools, which focus on the life cycle of small craft passenger vessels made of composite materials. The chapter concentrates on FRP (Fibreglass Reinforced Plastics) made vessels with length overall up to 30 m and total capacity up to 150 passengers, for the purposes of cruise ship liners disembarkation, scheduled routes or transportation of professional personnel to offshore sites. The collection of proposed tools consists of the "Vessel Meta-File", a user-friendly, web-based, information rich, technical meta-file that acts as the main knowledge-base between the ship-yard, which is the constructor of the vessel, the classification society, which is the controlling body imposing the restrictions of the vessel and the end-user. The Vessel Meta-File enables the storage of information regarding all N. Frangakis