The method of trust level of publications hosted in virtual communities
| Назва | The method of trust level of publications hosted in virtual communities |
| Назва англійською | The method of trust level of publications hosted in virtual communities |
| Автори | Anna Synko |
| Принадлежність | Lviv Polytechnic National University, Lviv, Ukraine |
| Бібліографічний опис | The method of trust level of publications hosted in virtual communities / Anna Synko // Scientific Journal of TNTU. — Tern.: TNTU, 2022. — Vol 105. — No 1. — P. 68–79. |
| Bibliographic description: | Synko A. (2022) The method of trust level of publications hosted in virtual communities. Scientific Journal of TNTU (Tern.), vol 105, no 1, pp. 68–79. |
| УДК | 004.021 |
| Ключові слова | data analysis, parsing, data processing, virtual community, score methodology, ImportXML function. |
The proposed model of data collection and analysis from thematic virtual communities using known information analysis techniques: scoring and parsing. Open communities were selected for the study, namely their architecture and main components: information content (title, description, posts, topics of the event) and audience (community members). To select relevant, informative, reliable publications, the scoring method is used which reflects the level of trust of the authors of the publication in the form of weighted indicators of a set of certain characteristics. Data collection is a combined approach, as virtual communities are dynamic in the content of the data and their content depends on the actions of the participants. To parse posts from virtual communities, it was decided to use ImportXML function in Microsoft Excel, which allows you to collect data from different sources, and then sample, analyze, and select the presentation of results using other built-in tools of this program. | |
| ISSN: | 2522-4433 |
| Перелік літератури |
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| References: |
1. Jiang W., Wang G., Bhuiyan Z. A., Wu J. Understanding graph–based trust evaluation in online social networks: Methodologies and challenges. ACM Computing Surveys (CSUR). Vol. 49. No. 1. 2016. P. 1–35. DOI: https://doi.org/10.1145/290615.
2. Lunkina T. I., Velkhovatska K. O. Metody upravlinnia ryzykamy spozhyvchoho kredytuvannia, “Young Scientist”. Vol. 2 (17). 2015. P. 157–160. [In Ukrainian].
3. Zhou B., Zhao H., Puig X., Fidler S., Barriuso A., Torralba A. Scene parsing through ade20k dataset. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2017. P. 633–641. DOI: https://doi.org/10.1109/CVPR.2017.544.
4. Reddy S., Tackstrom O., Petrov S., Steedman M., Lapata M. Universal semantic parsing. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, Association for Computational Linguistics. 2017. P. 89–101. DOI: https://doi.org/10.18653/v1/D171009.
5. Zhao H., Shi J., Qi X., Wang X., Jia J. Pyramid scene parsing network. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2017. P. 2881–2890. DOI: https://doi.org/10.1109/ CVPR.2017.660.
6. Prylutskyi P. V., Servis z ahrehuvannia platizhnykh system. Kyiv: Igor Sikorsky Kyiv Polytechnic Institute, 2020. 98 p. [In Ukrainian].
7. Britvin A., Tkachuk R. Parsynh danykh z veb storinok. V All-Ukrainian scientific-practical conference of young scientists, students and cadets “Cybersecurity and Information Technology”. CIT 2021. Lviv. November 26. 2021. P. 13–14. [In Ukrainian].
8. Phillips David M.W., Web Scraping with Excel. CreateSpace Independent Publishing Platform. March 6. 2016. P. 62.
9. Beznosyk O., Kulyk O. Automatized parsing of bibliographic references. The 8th International Scientific and Practical Conference “Computer Modeling in Chemistry, Technologies and Systems of Sustainable Development – ChTCTST-2020”. Kyiv: Igor Sikorsky Kyiv Polytechnic Institute, 2020. May 19–22. P. 364–372. [In Ukrainian].
10. Zakon Ukrainy “Pro informatsiiu”, Information of the Verkhovna Rada of Ukraine. № 2658-XII from 02.10.92 edited by 02.06.2016. URL: http://zakon3.rada.gov.ua/laws/show/2657-12. [In Ukrainian].
11. Trach O. R. Mathematical support and software for organization of the life cycle of virtual communities: Thesis for a Ph.D degree, Lviv Polytechnic National University, Ministry of Education and Science of Ukraine. Lviv. 2018. P. 172. [In Ukrainian].
12. Fedushko S. Development of a software for computer-linguistic verification of socio-demographic profile of web-community member. Webology. Vol. 11. No. 2. 2014. Article 126.
13. Fedushko S., Mastykash O., Syerov Y., Shilinh A. Model of Search and Analysis of Heterogeneous User Data to Improve the Web Projects Functioning. Advances in Computer Science for Engineering and Education IV. ICCSEEA 2021. Lecture Notes on Data Engineering and Communications Technologies, Springer, Cham. Vol 83. 2021. P. 56–74. DOI: https://doi.org/10.1007/978-3-030-80472-5_6.
14. Fedushko S., Syerov Yu., Skybinskyi O., Shakhovska N., Kunch Z. Efficiency of Using Utility for Username Verification in Online Community Management. Proceedings of the International Workshop on Conflict Management in Global Information Networks (CMiGIN 2019), Lviv, Ukraine, November 29, 2019. CEUR-WS.org, Vol-2588. P. 265–275.
15. Markovets O. V. Mathematical and software of interaction of citizens with authorities in heterogeneous web environments: Thesis for a Ph.D degree, Lviv Polytechnic National University, Ministry of Education and Science of Ukraine. Lviv. 2015. P. 144. [In Ukrainian].
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