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  1. Book ; Online: Cybersecurity of Digital Service Chains

    Kołodziej, Joanna / Repetto, Matteo / Duzha, Armend

    Challenges, Methodologies, and Tools

    (Lecture Notes in Computer Science ; 13300)

    2022  

    Author's details edited by Joanna Kołodziej, Matteo Repetto, Armend Duzha
    Series title Lecture Notes in Computer Science ; 13300
    Keywords Computer networks  ; Computers—Law and legislation ; Information technology—Law and legislation ; Data protection ; Application software
    Subject code 004.6
    Language English
    Size 1 Online-Ressource (XI, 257 p. 90 illus., 71 illus. in color)
    Edition 1st ed. 2022
    Publisher Springer International Publishing ; Imprint: Springer
    Publishing place Cham
    Document type Book ; Online
    HBZ-ID HT021360224
    ISBN 978-3-031-04036-8 ; 9783031040351 ; 9783031040375 ; 3-031-04036-8 ; 303104035X ; 3031040376
    DOI 10.1007/978-3-031-04036-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online: Cybersecurity of Digital Service Chains

    Kołodziej, Joanna / Repetto, Matteo / Duzha, Armend

    Challenges, Methodologies, and Tools

    (Lecture Notes in Computer Science)

    2022  

    Series title Lecture Notes in Computer Science
    Keywords Network hardware ; Legal aspects of IT ; Computer security ; Information retrieval ; cloud computing ; computer crime ; computer networks ; computer security ; cryptography ; cyber security ; data communication systems ; data flow architectures ; data management systems ; data security ; electromagnetic interference and compatibility ; general programming languages ; health informatics ; intrusion detection ; network protocols ; network security ; network simulations ; sensors and actuators ; signal processing ; telecommunication traffic
    Language 0|e
    Size 1 electronic resource (257 pages)
    Publisher Springer Nature
    Publishing place Cham
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021609698
    ISBN 9783031040368 ; 3031040368
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Article ; Online: Hate versus politics: detection of hate against policy makers in Italian tweets.

    Duzha, Armend / Casadei, Cristiano / Tosi, Michael / Celli, Fabio

    SN social sciences

    2021  Volume 1, Issue 9, Page(s) 223

    Abstract: Accurate detection of hate speech against politicians, policy making and political ideas is crucial to maintain democracy and free speech. Unfortunately, the amount of labelled data necessary for training models to detect hate speech are limited and ... ...

    Abstract Accurate detection of hate speech against politicians, policy making and political ideas is crucial to maintain democracy and free speech. Unfortunately, the amount of labelled data necessary for training models to detect hate speech are limited and domain-dependent. In this paper, we address the issue of classification of hate speech against policy makers from Twitter in Italian, producing the first resource of this type in this language. We collected and annotated 1264 tweets, examined the cases of disagreements between annotators, and performed in-domain and cross-domain hate speech classifications with different features and algorithms. We achieved a performance of ROC AUC 0.83 and analyzed the most predictive attributes, also finding the different language features in the anti-policymakers and anti-immigration domains. Finally, we visualized networks of hashtags to capture the topics used in hateful and normal tweets.
    Language English
    Publishing date 2021-08-20
    Document type Journal Article
    ISSN 2662-9283
    ISSN (online) 2662-9283
    DOI 10.1007/s43545-021-00234-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Online: Hate versus Politics

    Duzha, Armend / Casadei, Cristiano / Tosi, Michael / Celli, Fabio

    Detection of Hate against Policy makers in Italian tweets

    2021  

    Abstract: Accurate detection of hate speech against politicians, policy making and political ideas is crucial to maintain democracy and free speech. Unfortunately, the amount of labelled data necessary for training models to detect hate speech are limited and ... ...

    Abstract Accurate detection of hate speech against politicians, policy making and political ideas is crucial to maintain democracy and free speech. Unfortunately, the amount of labelled data necessary for training models to detect hate speech are limited and domain-dependent. In this paper, we address the issue of classification of hate speech against policy makers from Twitter in Italian, producing the first resource of this type in this language. We collected and annotated 1264 tweets, examined the cases of disagreements between annotators, and performed in-domain and cross-domain hate speech classifications with different features and algorithms. We achieved a performance of ROC AUC 0.83 and analyzed the most predictive attributes, also finding the different language features in the anti-policymakers and anti-immigration domains. Finally, we visualized networks of hashtags to capture the topics used in hateful and normal tweets.

    Comment: to appear in SN social sciences - special issue on hate speech
    Keywords Computer Science - Computation and Language ; 68T50 ; K.4.1 ; J.4
    Subject code 400
    Publishing date 2021-07-12
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: PolicyCLOUD: Analytics as a Service Facilitating Efficient Data-Driven Public Policy Management

    Kyriazis, Dimosthenis / Biran, Ofer / Bouras, Thanassis / Brisch, Klaus / Duzha, Armend / del Hoyo, Rafael / Kiourtis, Athanasios / Kranas, Pavlos / Maglogiannis, Ilias / Manias, George / Meerkamp, Marc / Moutselos, Konstantinos / Mavrogiorgou, Argyro / Michael, Panayiotis / Munné, Ricard / La Rocca, Giuseppe / Nasias, Kostas / Pariente Lobo, Tomas / Rodrigálvarez, Vega /
    Sgouros, Nikitas M. / Theodosiou, Konstantinos / Tsanakas, Panayiotis

    Artificial Intelligence Applications and Innovations

    Abstract: While several application domains are exploiting the added-value of analytics over various datasets to obtain actionable insights and drive decision making, the public policy management domain has not yet taken advantage of the full potential of the ... ...

    Abstract While several application domains are exploiting the added-value of analytics over various datasets to obtain actionable insights and drive decision making, the public policy management domain has not yet taken advantage of the full potential of the aforementioned analytics and data models. Diverse and heterogeneous datasets are being generated from various sources, which could be utilized across the complete policies lifecycle (i.e. modelling, creation, evaluation and optimization) to realize efficient policy management. To this end, in this paper we present an overall architecture of a cloud-based environment that facilitates data retrieval and analytics, as well as policy modelling, creation and optimization. The environment enables data collection from heterogeneous sources, linking and aggregation, complemented with data cleaning and interoperability techniques in order to make the data ready for use. An innovative approach for analytics as a service is introduced and linked with a policy development toolkit, which is an integrated web-based environment to fulfil the requirements of the public policy ecosystem stakeholders.
    Keywords covid19
    Publisher PMC
    Document type Article ; Online
    DOI 10.1007/978-3-030-49161-1_13
    Database COVID19

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