@article {818,
	title = {Disruptive Technologies for Parliaments: A Literature Review},
	journal = {Future Internet},
	volume = {15},
	year = {2023},
	month = {feb},
	pages = {66},
	abstract = {<p>Exploitation and use of disruptive technologies, such as the Internet of Things, recommender systems, and artificial intelligence, with an ambidextrous balance, are a challenge, nowadays. Users of the technologies, and stakeholders, could be part of a new organisational model that affects business procedures and processes. Additionally, the use of inclusive participatory organisational models is essential for the effective adoption of these technologies. Such models aim to transform organisational structures, as well. Public organisations, such as the parliament, could utilise information systems{\textquoteright} personalisation techniques. As there are a lot of efforts to define the framework, the methodology, the techniques, the platforms, and the suitable models for digital technologies adoption in public organisations, this paper aims to provide a literature review for disruptive technology inclusive use in parliaments. The review emphasises the assessment of the applicability of the technologies, their maturity and usefulness, user acceptance, their performance, and their correlation to the adoption of relevant innovative, inclusive organisational models. It is argued that the efficient digital transformation of democratic institutions, such as parliaments, with the use of advanced e-governance tools and disruptive technologies, requires strategic approaches for adoption, acceptance, and inclusive service adaptation.</p>
},
	keywords = {artificial intelligence, digital transformation, inclusiveness, Internet of Things, parliament, Recommender Systems},
	doi = {https://doi.org/10.3390/fi15020066},
	url = {https://www.mdpi.com/1999-5903/15/2/66},
	author = {Dimitris Koryzis and Dionisis Margaris and Costas Vassilakis and Konstantinos Kotis and Dimitris Spiliotopoulos}
}
@article {782,
	title = {Data-Assisted Persona Construction Using Social Media Data},
	journal = {Big Data and Cognitive Computing},
	volume = {4},
	year = {2020},
	month = {aug},
	pages = {21},
	abstract = {<p>User experience design and subsequent usability evaluation can benefit from knowledge about user interaction, types, deployment settings and situations. Most of the time, the user type and generic requirements are given or can be obtained and used to model interaction during the design phase. The deployment settings and situations can be collected through the needfinding phase, either via user feedback or via the automatic analysis of existing data. Personas may be defined using the aforementioned information through user research analysis or data analysis. This work utilizes an approach to activate an accurate persona definition early in the design cycle, using topic detection to semantically enrich the data that are used to derive the persona details. This work uses Twitter data from a music event to extract information that can be used to assist persona creation. A user study in persona construction compares the topic modelling metadata to a traditional user collected data analysis for persona construction. The results show that the topic information-driven constructed personas are perceived as having better clarity, completeness and credibility. Additionally, the human users feel more attracted and similar to such personas. This work may be used to model personas and recommend suitable ones to designers of other products, such as advertisers, game designers and moviegoers.</p>
},
	keywords = {Cultural Events, Persona, personalization, Topic Modelling, Usability, User Experience, User Interface Design},
	doi = {10.3390/bdcc4030021},
	author = {Dimitris Spiliotopoulos and Dionisis Margaris and Costas Vassilakis}
}
@conference {spiliotopoulos_2019_asonam,
	title = {Data-driven Country Safety Monitoring Terrorist Attack Prediction},
	booktitle = {Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019)},
	year = {2019},
	month = {aug},
	abstract = {Terrorism is a key risk for prospective visitors of tourist desti-nations. This work reports on the analysis of past terrorist at-tack data, focusing on tourist-related attacks and attack types in Mediterranean EU area and the development of algorithms to predict terrorist attack risk levels. Data on attacks in 10 coun-tries have been analyzed to quantify the threat level of tourism-related terrorism based on the data from 2000 to 2017 and for-mulate predictions for subsequent periods. Results show that predictions on potential target types can be derived with ade-quate accuracy. Such results are useful for initiating, shifting and validating active terrorism surveillance based on real pre-dicted attack and target types per country.},
	keywords = {Data Analysis, Risk Calculation, Safety Perception, Terrorist Attacks, Threat Ranking},
	author = {Dimitris Spiliotopoulos and Costas Vassilakis and Dionisis Margaris}
}
