Awareness, values and attitudes of user generated content website users and non-users towards privacy in Austria : a quantitative study

This research was carried out as part of CONSENT (Consumer sentiment regarding privacy on user generated content (UGC) services in the digital economy) a project that was funded by the European Union under the Seventh Framework Programme (2007-2013), Grant Agreement Number 244643.This document presents the Austrian results of a study undertaken as part of the CONSENT project. Analyses and results are based on an online survey regarding the awareness, values and attitudes of user generated content (UGC) website users towards privacy. The questionnaire consisted of 75 questions and was available online in several European languages, including German, between July and December 2011. The Austrian sample consists of 131 respondents (1.5% of the total sample), of which 62.1% male and 37.9% female, with an average age of 31 and 63.2% tertiary education. With 85% UGC users (total sample 90%), 13.04 mean years of internet usage (total sample 10.67) and 86.9% using the internet at home every day or almost every day (total sample 93%), it is considered a sample of predominantly experienced, frequent internet users who are very likely to also be UGC users.This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 285582.peer-reviewe

Awareness, values and attitudes of user generated content website users and non-users towards privacy in Austria : a quantitative study

This research was carried out as part of CONSENT (Consumer sentiment regarding privacy on user generated content (UGC) services in the digital economy) a project that was funded by the European Union under the Seventh Framework Programme (2007-2013), Grant Agreement Number 244643.This document presents the Austrian results of a study undertaken as part of the CONSENT project. Analyses and results are based on an online survey regarding the awareness, values and attitudes of user generated content (UGC) website users towards privacy. The questionnaire consisted of 75 questions and was available online in several European languages, including German, between July and December 2011. The Austrian sample consists of 131 respondents (1.5% of the total sample), of which 62.1% male and 37.9% female, with an average age of 31 and 63.2% tertiary education. With 85% UGC users (total sample 90%), 13.04 mean years of internet usage (total sample 10.67) and 86.9% using the internet at home every day or almost every day (total sample 93%), it is considered a sample of predominantly experienced, frequent internet users who are very likely to also be UGC users.This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 285582.peer-reviewe

Malicious Cyber Operations, “Hackbacks” and International Law: An Austrian Example as a Basis for Discussion on Permissible Responses

In January 2020, Austria publicly announced that some of its governmental institutions have been hit by a significant malicious cyber operation and that it cannot be denied – at least for the moment – that a state was behind this operation. One month later, the Austrian Foreign Ministry declared the cyber operation to be officially over. While Austria noted that it took “countermeasures” against the operation, it is not entirely clear what it meant by that. This article elaborates the question what response options a state like Austria would have against a malicious cyber operation under the current framework of international law. It, hence, tries to answer when a “hackback” is lawful under international law and when it is not

Automatically identifying eviction cases and outcomes within case law of Dutch Courts of First Instance

In this paper we attempt to identify eviction judgements within all case law published by Dutch courts in order to automate data collection, previously conducted manually. To do so we performed two experiments. The first focused on identifying judgements related to eviction, while the second focused on identifying the outcome of the cases in the judgements (eviction vs. dismissal of the landlord’s claim). In the process of conducting the experiments for this study, we have created a manually annotated dataset with eviction-related judgements and their outcomes

Proceedings of LOAIT '07 : II Workshop on Legal Ontologies and Artificial Intelligence Techniques

Proceedings of the 2nd Workshop on Legal Ontologies and Artificial Intelligence Techniques June 4th, 2007, Stanford Universit