OSN platforms are under attack by intruders born and raised within their own ecosystems. These attacks have multiple scopes from mild critiques to violent offences targeting individual or community rights and opinions. Negative publicity on microblogging platforms, such as Twitter, is due to the infamous Twitter bots which highly impact posts’ circulation and virality. A wide and ongoing research effort has been devoted to develop appropriate countermeasures against emerging “armies of bots”. However, the battle against bots is still intense and unfortunately, it seems to lean on the bot-side. Since, in an effort to win any war, it is critical to know your enemy, this work aims to demystify, reveal, and widen inherent characteristics of Twitter bots such that multiple types of bots are recognized and spotted early. More specifically in this work we: (i) extensively analyze the importance and the type of data and features used to generate ML models for bot classification, (ii) address the open problem of multi-class bot detection, identifying new types of bots, and share two new datasets towards this objective, (iii) provide new individual ML models for binary and multi-class bot classification and (iv) utilize explainable methods and provide comprehensive visualizations to clearly demonstrate interpretable results. Finally, we utilize all of the above in an effort to improve the so called Bot-Detective online service. Our experiments demonstrate high accuracy, explainability and scalability, comparable with the state of the art, despite multi-class classification challenges.

The rapidly moving technological advances have forced key industrial sectors to accelerate their digital transformation processes. Despite the growing interest of organizations on investing in technological advances, the Oil and Gas (O&G) industry is losing ground on the digitalization race. Except from the technological inhibitors, the relatively slow transition is related to human capital and the lack of skillful workforce able to fulfill emerging digital job positions. Additionally, the empirical evidence indicates a knowledge gap regarding the current demand for O&G digital experts and the associated responsibilities and competencies. The objective of this study is two-fold: First, we investigate the status of the O&G labor market digital career opportunities. Second, we shed light on the most prominent digital job roles and the corresponding skillsets, so as to design competence maps with interrelated technological skills. To meet our objectives, we analyzed 1999 job openings from three well-known O&G job boards through a framework augmented with natural language processing and graph theory community detection methodologies. The findings for emerging technology trends constitute an empirical benchmark for a wide range of target groups that are interested in acquiring knowledge related to the state-of-the-art digital demand and the endorsed competencies in the uprising O&G digitalized era.

Sustainable greenhouse production has been brought to the forefront as one of the pillars in achieving the objectives set by the Green Deal strategy in 2020, for drastically decreasing net emissions from agriculture. The scope of this review was to capture the current situation regarding the sustainability of greenhouse production in the European Union and to present ways to decrease the carbon footprint. For this reason, a systematic search of studies was conducted, focusing on the investigation of the environmental assessment of conventional greenhouses in EU along with a bibliometric analysis to identify the relationships between the studies. In total, 52 papers were selected for an in-depth analysis that led to addressing the posed research questions. The study reveals that Spain and Italy were the most active countries in the literature for the calculation of the carbon footprint in greenhouses, the value of which showed a large variation per crop and per country and was significantly affected by the use of non-renewable energy sources. It was observed that practical solutions to reduce the carbon footprint of greenhouses have already been implemented and proposed, which indicates a positive inclination towards achieving the Green Deal objectives.