Application of Automated Tools in Researching Internet Discourses: Experience of Using the Recurrent Neural Networks for Studying Discussions on Pension Reform

Begen, Petr Nikolayevich; Misnikov, Yuri; Filatova, Olga

doi:10.20948/abrau-2019-91

Cited by 3 publications

(3 citation statements)

References 5 publications

(2 reference statements)

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“…Paper ID F-measure [44,45,47,48,57,58,60,64,66,73,77,80,82,86] Precision [43,45,57,60,62,66,67,73,[76][77][78]80,82,86] Accuracy [43,44,46,62,63,69,70,73,[76][77][78]80,82] Recall [45,52,57,60,62,66,73,77,78,80,82,…”

Section: Discussionmentioning

confidence: 99%

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The Use of Artificial Intelligence in eParticipation: Mapping Current Research

Vasilakopoulos,

Tavantzis,

Promikyridis

et al. 2024

Future Internet

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Electronic Participation (eParticipation) enables citizens to engage in political and decision-making processes using information and communication technologies. As in many other fields, Artificial Intelligence (AI) has recently started to dictate some of the realities of eParticipation. As a result, an increasing number of studies are investigating the use of AI in eParticipation. The aim of this paper is to map current research on the use of AI in eParticipation. Following PRISMA methodology, the authors identified 235 relevant papers in Web of Science and Scopus and selected 46 studies for review. For analysis purposes, an analysis framework was constructed that combined eParticipation elements (namely actors, activities, effects, contextual factors, and evaluation) with AI elements (namely areas, algorithms, and algorithm evaluation). The results suggest that certain eParticipation actors and activities, as well as AI areas and algorithms, have attracted significant attention from researchers. However, many more remain largely unexplored. The findings can be of value to both academics looking for unexplored research fields and practitioners looking for empirical evidence on what works and what does not.

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Section: Discussionmentioning

confidence: 99%

“…Paper ID Deliberative [42,48,55,61,64,65,69,71,79,81,86] Democratic [41,44,50,54,65,81,85] Civic Engagement [41,44,47,[49][50][51][53][54][55]58,60,63,65,66,[68][69][70]74,76,[78][79][80][81][82][83]85,86]…”

Section: Effectsmentioning

confidence: 99%

The Use of Artificial Intelligence in eParticipation: Mapping Current Research

Vasilakopoulos,

Tavantzis,

Promikyridis

et al. 2024

Future Internet

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“…Применению методов машинного обучения, в частности, искусственных нейронных сетей, в сентимент-анализе (анализе тональности текста) и компьютерной лингвистике послужили развитие информационно-коммуникационных технологий, значительное увеличение количества данных и рост вычислительных мощностей [11,12]. На их основе нам удалось провести пилотное исследование с применением машинного обучения для сентимент-анализа дискуссий граждан на такую актуальную общественно-политическую тему, как российская пенсионная реформа [13]. Цель данного исследования заключалась в разработке автоматизированного инструментария для проведения анализа интернетдискурса, в частности, проведение эксперимента по применению искусственных нейронных сетей в определении позиций граждан (сентимент-анализ) в онлайн-обсуждениях на тему повышения пенсионного возраста.…”

Section: изучениеunclassified