ORCID Profile
0000-0002-4271-9174
Current Organisation
Deakin University
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Publisher: IEEE
Date: 11-07-2021
Publisher: IEEE
Date: 09-2019
Publisher: ACM
Date: 27-06-2020
Publisher: ACM
Date: 25-08-2016
Publisher: IEEE
Date: 07-2012
Publisher: IEEE
Date: 05-2017
Publisher: Springer Science and Business Media LLC
Date: 03-08-2017
Publisher: Springer Science and Business Media LLC
Date: 08-06-2021
Publisher: Springer International Publishing
Date: 2017
Publisher: Elsevier BV
Date: 04-2021
Publisher: ACM
Date: 27-06-2020
Publisher: Hindawi Limited
Date: 28-10-2021
DOI: 10.1002/HBE2.304
Publisher: Association for Computing Machinery (ACM)
Date: 07-12-2022
DOI: 10.1145/3530813
Abstract: Many scientific and practical areas have shown increasing interest in reaping the benefits of blockchain technology to empower software systems. However, the unique characteristics and requirements associated with Blockchain-based Software (BBS) systems raise new challenges across the development lifecycle that entail an extensive improvement of conventional software engineering. This article presents a systematic literature review of the state-of-the-art in BBS engineering research from the perspective of the software engineering discipline. We characterize BBS engineering based on the key aspects of theoretical foundations, processes, models , and roles . Based on these aspects, we present a rich repertoire of development tasks, design principles, models, roles, challenges, and resolution techniques. The focus and depth of this survey not only give software engineering practitioners and researchers a consolidated body of knowledge about current BBS development but also underpin a starting point for further research in this field.
Publisher: ACM
Date: 26-10-2018
Publisher: IEEE
Date: 06-2012
Publisher: Springer Science and Business Media LLC
Date: 07-01-2020
Publisher: ACM
Date: 29-05-2018
Publisher: Hindawi Limited
Date: 09-03-2023
DOI: 10.1155/2023/7283166
Abstract: The emotional impact of the COVID-19 pandemic and ensuing social restrictions has been profound, with widespread negative effects on mental health. We made use of the natural language processing and large-scale Twitter data to explore this in depth, identifying emotions in COVID-19 news content and user reactions to it, and how these evolved over the course of the pandemic. We focused on major UK news channels, constructing a dataset of COVID-related news tweets (tweets from news organisations) and user comments made in response to these, covering Jan 2020 to April 2021. Natural language processing was used to analyse topics and levels of anger, joy, optimism, and sadness. Overall, sadness was the most prevalent emotion in the news tweets, but this was seen to decline over the timeframe under study. In contrast, amongst user tweets, anger was the overall most prevalent emotion. Time epochs were defined according to the time course of the UK social restrictions, and some interesting effects emerged regarding these. Further, correlation analysis revealed significant positive correlations between the emotions in the news tweets and the emotions expressed amongst the user tweets made in response, across all channels studied. Results provide unique insight onto how the dominant emotions present in UK news and user tweets evolved as the pandemic unfolded. Correspondence between news and user tweet emotional content highlights the potential emotional effect of online news on users and points to strategies to combat the negative mental health impact of the pandemic.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Global Vision Press
Date: 30-09-2013
No related grants have been discovered for Davoud Mougouei.