Development of the system to integrate and generate content considering the cryptocurrent needs of users

Lytvyn, Vasyl; Vysotska, Victoria; Kuchkovskiy, Volodymyr; Bobyk, Іgor; Маланчук, Оксана; Ryshkovets, Yuriy; Pelekh, Irina; Brodyak, Oksana; Bobrivetc, Vitaliy; Panasyuk, Valentyna

doi:10.15587/1729-4061.2019.154709

Cited by 10 publications

(6 citation statements)

References 57 publications

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“…Compare three publications [1,74,77] in scientific technical area based on the linguo-statistical analysis of 3-grams. Article 1, 2 were written by one team of authors [1,74], Article 3 was written by another author [77] (Table 7). The language of the text is Ukrainian (there are 33 letters in the alphabet, then the number of all possible N-grams is 35,937).…”

Section: Results Of Experimental Testing Of the Proposed Content-monimentioning

confidence: 99%

“…Similarly, the issues related to authorship attribution are important in linguistic, historical and forensic studies [73]. The availability of electronic devices makes it possible to push back the authorship attribution with the involvement of a large number of experts, to accelerate and simplify this process through its automation [74]. The notion of the authorship attribution is defined as the process of finding the author by many general and private features of a text that constitute the author's style [75].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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Development of the quantitative method for automated text content authorship attribution based on the statistical analysis of N-grams distribution

Lytvyn

Vysotska

Budz

et al. 2019

EEJET

Self Cite

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Розглянуто особливостi застосування технологiй лiнгвостатистики для iдентифiкацiї стилiстики автора текстового контенту науково-технiчного профiлю. Квантитативний лiнгвiстичний аналiз тексту використовує переваги контент-монiторiнгу на основi методiв NLP для визначення та аналiзу множини стопових слiв, ключових слiв, стiйких словосполучень та дослiдження N-грам. Останнi використовують в методах лiнгвометрiї для визначення приналежностi аналiзованого тексту конкретному авторовi у вiдсотках. Розроблено квантитативний метод автоматичного визначення авторства текстового контенту на основi статистичного аналiзу розподiлу 3-грам. Запропоновано пiдхiд реалiзацiї визначення автора україномовного тексту науково-технiчного профiлю. Отримано експериментальнi результати запропонованого методу для визначення приналежностi аналiзованого тексту конкретному автору за наявностi еталонного авторського тексту. Застосування лiнгвостатистичного аналiзу 3-грам до множини статей дозволить сформувати пiдмножину подiбних за лiнгвiстичними характеристиками публiкацiй. Накладання на пiдмножину додаткових умов у виглядi проведення статистичних та квантитативних аналiзiв (множини ключових слiв, стiйких словосполучень, стилеметричного, лiгвометричного тощо) дозволить значно скоротити цю пiдмножину, уточнивши список ймовiрнiших авторських робiт. Для якiсного та ефективного аналiзу контенту при визначеннi ступеня авторства конкретному автору пропонуємо аналiзувати еталонного тексту та дослiджуваного в декiлька етапiв: лiнгвометричний аналiз коефiцiєнтiв рiзноманiття авторського мовлення, стилометричний аналiз, аналiз стiйких словосполучень, лiнгвостатистичний аналiз 3-грам. Для автоматизованого опрацювання тексту має велике значення не тiльки частота появи тiєї чи iншої категорiї, а взагалi присутнiсть в дослiджуваному текстi. Кiлькiсний пiдрахунок дозволяє зробити об'єктивнi висновки щодо спрямованостi матерiалiв за кiлькiстю уживань одиниць аналiзу в дослiджуваних текстах. Якiсний аналiз робить те саме, але внаслiдок дослiдження того, чи зустрiчається (i в якому контекстi) певна важлива оригiнальна категорiя взагалi Ключовi слова: NLP, контент, контент-монiторiнг, стоп-слова, контент-аналiз, статистийний лiнгвiстичний аналiз, квантитативна лiнгвiстика, статистична лiнгвiстика, лiнгвометрiя UDC 004.

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Section: Results Of Experimental Testing Of the Proposed Content-monimentioning

confidence: 99%

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of the quantitative method for automated text content authorship attribution based on the statistical analysis of N-grams distribution

Lytvyn

Vysotska

Budz

et al. 2019

EEJET

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore, we find that the number of single authors per article is very far from the number of authors of multi-authored articles, which could confirm the importance of network analysis. There are three papers with 9 (Raman et al , 2019), 10 (Lytvyn et al. , 2019) and 13 (Thomason et al ., 2018) authors.…”

Section: Descriptive Bibliometric Analysismentioning

confidence: 99%

Exploring blockchain in the accounting domain: a bibliometric analysis

Lardo

Corsi

Varma

et al. 2022

AAAJ

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PurposeConsidering the growing interests in managerial and accounting issues related to blockchain technology (BT), the study aims at identifying the main research venues in this specific field. In particular, the purpose is to understand the spatial and temporal production and distribution of research documents, highlighting the most relevant topics, the most influential authors and research.Design/methodology/approachThis research carries out a bibliometric analysis of 189 research documents in the business, management and accounting areas. Data collection and refining is carried out from the Scopus database. The data analysis is based on a hybrid literature review approach using a descriptive bibliometric method, data analysis visualization (through VOSViewer software) and thematic analysis.FindingsResults indicate that research studies focused on BT and accounting have been growing exponentially over the last three years, with authors who previously focused on generalist themes, and are now facing more specific issues. Through cluster analysis, the authors propose the framework of accounting domain and blockchain technology (ADOB) to systematize and visualize the map of current studies about the BT in the accounting domain.Research limitations/implicationsThe analysis highlights some aspects less investigated at the first research stage in the field of BT and accounting, such as the growing need of new accounting and control processes to address the practical issues of BT implementation and the need for education and training to stimulate a proper use of BT by accountants and practitioners.Originality/valueThis study is the first to adopt a bibliometric and thematic analysis to investigate BT in the accounting domain. The authors provide significant insights that could guide and foster the use of BT for accountants and practitioners, defining future research lines and a research agenda for academic researchers.

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“…Emphasis has been given to the regularity of updating the data collection rate from online trading platforms and other traffic sources [37]. Accordingly, the use of blockchain innovation to optimize digital marketing and advertising has inadvertently boosted customer privacy [38].…”

Section: ) Cryptocurrency Trade Digital Behavior Organic Campaigns An...mentioning

confidence: 99%

Innovative Cryptocurrency Trade Websites’ Marketing Strategy Refinement, via Digital Behavior

et al. 2022

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Nowadays, the cryptocurrency market is thriving, through the rise in cryptocurrency trading, opening the way for cryptocurrency trading websites' optimization. Optimization of customer satisfaction is a vital part of cryptocurrency trade organizations' digital marketing problems. It is vital to keep digital advertisement costs low while driving more traffic to a website. This study aims to define a digital marketing strategy for cryptocurrency trading websites by utilizing digital behavior metrics. Web analytics data were gathered from 10 world-leading cryptocurrency trade websites over 80 days. Statistical analysis of cryptocurrency trade web analytics, Fuzzy Cognitive Mapping modeling, and Agent-Based Model development have been deployed. Enhancement of cryptocurrency trade digital engagement levels can boost organizations' SEO and SEM strategy campaigns. Outputs of the study provide a handful of insights regarding cryptocurrency trading websites' digital promotion strategy optimization and the parameters of digital behavior mostly connected with websites' digital marketing costs and traffic. Cryptocurrency trade organizations should utilize both organic and paid campaigns, observe regularly their website KPIs connected with visitors' behavior and enhance their website users' experience, by increasing their engagement.

show abstract

Development of the system to integrate and generate content considering the cryptocurrent needs of users

Cited by 10 publications

References 57 publications

Development of the quantitative method for automated text content authorship attribution based on the statistical analysis of N-grams distribution

Development of the quantitative method for automated text content authorship attribution based on the statistical analysis of N-grams distribution

Exploring blockchain in the accounting domain: a bibliometric analysis

Innovative Cryptocurrency Trade Websites’ Marketing Strategy Refinement, via Digital Behavior

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