Methodology for identifying and tracking social media misinformation in tweets about the impact of the COVID-19 pandemic on reproductive health

Бесплатный доступ

The purpose of the study was to develop a methodology for identifying and tracking social media misinformation in tweets about the impact of the coronavirus and COVID-vaccine on reproductive health, one of the reasons for which is the lack of awareness about aspects of the coronavirus infection. We use a combination of machine and expert methods, the latest scientific articles as the standard for detecting disinformation. The proposed methodology includes the study of scientific articles as a source of reliable truthful information about the topic (information standard) and Twitter messages (assessment of information compliance with the standard). The result of the study is the methodology for detecting disinformation in the messages of social network users. Based on this methodology, the following aspects of the problem have been developed: 1) the formation of a scientific standard; 2) the principle of comparing the directions of scientific research and discussions on Twitter; 3) the principle of contextual comparison of user and scientific ideas about problems. In contrast to the existing works, the principles based on the information from the content of scientific articles and messages from social networks processing are formulated.

Еще

Misinformation, misinformation detecting, reproductive health, fertility, coronavirus, covid, vaccine, twitter, contextual comparison

Короткий адрес: https://sciup.org/148327116

IDR: 148327116   |   DOI: 10.18137/RNU.V9187.23.02.P.59

Список литературы Methodology for identifying and tracking social media misinformation in tweets about the impact of the COVID-19 pandemic on reproductive health

  • WHO (2021) Infodemic management 101. URL : https://openwho.org/courses/infodemic-management-101 (accessed 17.01.2023).
  • Ali I. (2020). The COVID-19 Pandemic: Making Sense of Rumor and Fear. Medical anthropology. Vol. 39. No. 5. Pp. 376–379. DOI: 10.1080/01459740.2020.1745481
  • Katsaros D., Stavropoulos G., Papakostas D. (2019) Which machine learning paradigm for fake news detection? In: IEEE/WIC/ACM International Conference on Web Intelligence (WI), Thessaloniki, Greece, 14–17 October 2019. Pp. 383–387. URL : https://ieeexplore.ieee.org/document/8909583 (accessed 17.01.2023).
  • Shu K., Sliva A., Wang S., Tang J., Liu H. (2017) Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter. Vol. 19. No. 1. Pp. 22–36. DOI: 10.1145/3137597.3137600
  • Molina M.D., Sundar S.S., Le T., Lee D. (2021). “Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content. American Behavioral Scientist. Vol. 65. No. 2. Pp. 180–212. DOI: 10.1177/0002764219878224
  • Conroy N.J., Rubin V.L., Chen Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology. Vol. 52. Pp. 1-4. DOI: 10.1002/pra2.2015.145052010082
  • Wang W.Y. (2017). “Liar, liar pants on fire”: A new benchmark dataset for fake news detection. arXiv. DOI: 10.48550/arXiv.1708.01967
  • Kaliyar R.K. (2018) Fake news detection using a deep neural network. In: 4th International Conference on Computing Communication and Automation (ICCCA), Greater Noida, India, 14-15 December 2018. Pp. 1–7. DOI: 10.1109/CCAA.2018.8777343
  • Liang Wu, Fred Morstatter, Kathleen M. Carley, and Huan Liu (2019). Misinformation in Social Media: Definition, Manipulation, and Detection. ACM SIGKDD Explorations Newsletter. Vol. 21, No. 2 (December 2019), Pp. 80–90. DOI: 10.1145/3373464.3373475
  • Choudrie J., Banerjee S., Kotecha K., Walambe R., Karende H., Ameta J. (2021). Machine learning techniques and older adults processing of online information and misinformation: A Covid 19 study. Computers in human behavior. Vol. 119. Art. no. 106716. DOI: 10.1016/j.chb.2021.106716
  • Vosoughi S., Roy D., Aral S. (2018). The spread of true and false news online. Science. Vol. 359. No. 6380. Pp. 1146–1151. DOI: 10.1126/science.aap9559
  • Barua Z. (2022). COVID-19 Misinformation on Social Media and Public’s Health Behavior: Understanding the Moderating Role of Situational Motivation and Credibility Evaluations. Human Arenas. Pp. 1–24. DOI: 10.1007/s42087-022-00291-w
  • Zolotarev O., Solomentsev Y., Khakimova A., Charnine M. (2019) Identification of Semantic Patterns in Full-text Documents Using Neural Network Methods. In: GraphiCon 2019. Computer Graphics and Vision : Proceedings of the 29th International Conference on Computer Graphics and Vision. Bryansk, Russia, 23–26 September 2019. URL : http://ceur-ws.org/Vol-2485/paper64.pdf (accessed 17.01.2023).
  • Khakimova A.Kh., Zolotarev O.V., Berberova M.A. (2021) Coronavirus Infection Study: Bibliometric Analysis of Publications on Covid-19 using PubMed and Dimensions Databases. Scientific Visualization. Vol. 12. No. 5. Pp. 112–129. DOI: 10.26583/sv.12.5.10
  • Li X., Chen Z., Geng J., Mei Q., Li H., Mao C., Han M. (2022). COVID-19 and Male Reproduction: A Thorny Problem. American journal of men’s health. Vol. 16. No. 1. DOI: 10.1177/15579883221074816
  • Adamyan L., Elagin V., Vechorko V., Stepanian A., Dashko A., Doroshenko D., Aznaurova Y., Sorokin M., Garazha A., Buzdin A. (2022). A Review of Recent Studies on the Effects of SARS -CoV-2 Infection and SARS -CoV-2 Vaccines on Male Reproductive Health. Medical science monitor. Vol. 28, e935879. DOI: 10.12659/MSM.935879
  • Ghosh S., Parikh S., Nissa M.U., Acharjee A., Singh A., Patwa D., Makwana P., Athalye A., Barpanda A., Laloraya M., Srivastava S., Parikh F. (2022). Semen Proteomics of COVID-19 Convalescent Men Reveals Disruption of Key Biological Pathways Relevant to Male Reproductive Function. ACS omega. Vol. 7. No. 10. Pp. 8601–8612. DOI: 10.1021/acsomega.1c06551
  • Collins A.B., Zhao L., Zhu Z., Givens N.T., Bai Q., Wakefield M.R., Fang Y. (2022). Impact of COVID-19 on Male Fertility. Urology. Vol. 164. Pp. 33–39. DOI: 10.1016/j.urology.2021.12.025
  • Goebel H., Koeditz B., Huerta M., Kameri E., Nestler T., Kamphausen T., Friemann J., Hamdorf M., Ohrmann T., Koehler P., Cornely O.A., Montesinos-Rongen M., Nicol D., Schorle H., Boor P., Quaas A., Pallasch C., Heidenreich A., von Brandenstein M. (2022). COVID-19 Infection Induce miR-371a-3p Upregulation Resulting in Influence on Male Fertility. Biomedicines. Vol. 10. No. 4. Pp. 858. DOI: 10.3390/biomedicines10040858
  • Jiang Q., Linn T., Drlica K., Shi L. (2022). Diabetes as a potential compounding factor in COVID-19-mediated male subfertility. Cell & bioscience. Vol. 12. No. 1. Art. no. 35. DOI: 10.1186/s13578-022-00766-x
  • Sengupta P., Dutta S., Roychoudhury S., D’Souza U., Govindasamy K., Kolesarova A. (2022). COVID-19, Oxidative Stress and Male Reproduction: Possible Role of Antioxidants. Antioxidants. Vol. 11. No. 3. Art. no. 548. DOI: 10.3390/antiox11030548
  • Verrienti P., Cito G., Di Maida F., Tellini R., Cocci A., Minervini A., Natali A. (2022). The impact of COVID-19 on the male genital tract: A qualitative literature review of sexual transmission and fertility implications. Clinical and experimental reproductive medicine. Vol. 49. No. 1. Pp. 9–15. DOI: 10.5653/cerm.2021.04511
  • Hu B., Liu K., Ruan Y., Wei X., Wu Y., Feng H., Deng Z., Liu J., Wang T. (2022). Evaluation of midand long-term impact of COVID-19 on male fertility through evaluating semen parameters. Translational andrology and urology. Vol. 11. No. 2. Pp. 159–167. DOI: 10.21037/tau-21-922
  • Zhu G., Du S., Wang Y., Huang X., Hu G., Lu X., Li D., Zhu Y., Qu D., Cai Q., Liu L., Du M. (2022). Delayed Antiviral Immune Responses in Severe Acute Respiratory Syndrome Coronavirus Infected Pregnant Mice. Frontiers in microbiology. Vol. 12. Art. no. 806902. DOI: 10.3389/fmicb.2021.806902
  • Ziert Y., Abou-Dakn M., Backes C., Banz-Jansen C., Bock N., Bohlmann M., Engelbrecht C., Gruber T.M., Iannaccone A., Jegen M., Keil C., Kyvernitakis I., Lang K., Lihs A., Manz J., Morfeld C., Richter M., Seliger G., Sourouni M., von Kaisenberg C. S. et. al. (2022) Maternal and neonatal outcomes of pregnancies with COVID-19 after medically assisted reproduction: Results from the prospective COVID-19-Related Obstetrical and Neonatal Outcome Study. American journal of obstetrics and gynecology. Vol. 27. No. 3. Pp. 495. DOI: 10.1016/j.ajog.2022.04.021
  • Youngster M., Avraham S., Yaakov O., Landau Rabbi M., Gat I., Yerushalmi G., Sverdlove R., Baum M., Maman E., Hourvitz A., Kedem A. (2022). IVF under COVID-19: treatment outcomes of fresh ART cycles. Human reproduction. Vol. 37. No. 5. Pp. 947–953. DOI: 10.1093/humrep/deac043
  • Jerzak M., Szafarowska M. (2022). Preliminary Results for Personalized Therapy in Pregnant Women with Polycystic Ovary Syndrome During the COVID-19 Pandemic. Archivum Immunologiae et Therapiae Experimentalis. Vol. 70. No. 1. Art. no. 13. DOI: 10.1007/s00005-022-00650-z
  • Carp-Veliscu A., Mehedintu C., Frincu F., Bratila E., Rasu S., Iordache I., Bordea A., Braga M. (2022). The Effects of SARS -CoV-2 Infection on Female Fertility: A Review of the Literature. International journal of environmental research and public health. Vol. 19. No. 2. Art. no. 984. DOI: 10.3390/ijerph19020984
  • Sun J., Liu Q., Zhang X., Dun S., Liu L. (2022). Mitochondrial hijacking: A potential mechanism for SARS -CoV-2 to impair female fertility. Medical hypotheses. Vol. 160. Art. no. 110778. DOI: 10.1016/j.mehy.2022.110778
  • Safrai M., Herzberg S., Imbar T., Reubinoff B., Dior U., Ben-Meir A. (2022). The BNT 162b2 mRN A Covid-19 vaccine does not impair sperm parameters. Reproductive biomedicine online. Vol. 44. No. 4. Pp. 685–688. DOI: 10.1016/j.rbmo.2022.01.008
  • Reschini M., Pagliardini L., Boeri L., Piazzini F., Bandini V., Fornelli G., Dolci C., Cermisoni G.C., Viganò P., Somigliana E., Coccia M.E., Papaleo E. (2022). COVID-19 Vaccination Does Not Affect Reproductive Health Parameters in Men. Frontiers in public health. Vol. 10. Art. no. 839967. DOI: 10.3389/fpubh.2022.839967
  • Braun A.S., Feil K., Reiser E., Weiss G., von Steuben T., Pinggera G.M., Köhn F.M., Toth B. (2022). Corona and Reproduction, or Why the Corona Vaccination Does Not Result in Infertility. Geburtshilfe und Frauenheilkunde. Vol. 82. No. 5. Pp. 490–500. DOI: 10.1055/a-1750-9284
  • Avraham S., Kedem A., Zur H., Youngster M., Yaakov O., Yerushalmi G.M., Gat I., Gidoni Y., Hochberg A., Baum M., Hourvitz A., Maman E. (2022). Coronavirus disease 2019 vaccination and infertility treatment outcomes. Fertility and sterility. Vol. 117. No. 6. Pp. 1291–1299. DOI: 10.1016/j.fertnstert.2022.02.025
  • Han A.R., Lee D., Kim S.K., Choo C.W., Park J.C., Lee J.R., Choi W.J., Jun J.H., Rhee J.H., Kim S.H. (2022). Effects and safety of COVID-19 vaccination on assisted reproductive technology and pregnancy: A comprehensive review and joint statements of the KSR M, the KSR I, and the KOSAR. Clinical and experimental reproductive medicine. Vol. 49. No. 1. Pp. 2–8. DOI: 10.5653/cerm.2022.05225
Еще
Статья научная