دانش تشخیص اطلاعات، تعدیلگر کنشگری کاربران ایرانی رسانههای اجتماعی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان
1 گروه ‌علوم ارتباطات اجتماعی، دانشکده علوم ارتباطات دانشگاه علّامه طباطبائی، تهران، ایران
2 گروه علوم ارتباطات اجتماعی، استادتمام دانشگاه علّامه طباطبائی، تهران، ایران
چکیده
پیش‌بینی اشتراک‌گذاری اطلاعات توسط کاربران رسانه‌های اجتماعی در ایران اهداف گوناگونی دارد؛ ازجمله می‌توان به نگرش‌ها، تجارب و کنشگری آن‌ها اشاره کرد. در این مقاله، رفتار اشتراک‌گذاری اطلاعات کاربران ایرانی در رسانه‌های اجتماعی مطالعه شده و نقش تعدیل‌گر دانش تشخیص اطلاعات بررسی می‌شود. هدف از انجام این پژوهش، پیش‌بینی عوامل مؤثر بر اشتراک‌گذاری اطلاعات توسط کاربران ایرانی و بررسی نقش تعدیل‌کنندۀ دانش تشخیص اطلاعات در رسانه‌های اجتماعی است. درواقع، نگرش کاربران نسبت به اشتراک‌گذاری اطلاعات تحت تأثیر اهداف مختلفی قرار دارد. درک این عوامل می‌تواند به توسعۀ راهبردهای مؤثر در زمینۀ بهینه‌سازی اشتراک‌گذاری اطلاعات در رسانه‌های اجتماعی کمک کرده و به بهبود کیفیت اطلاعات به اشتراک گذاشته‌شده منجر شود. روش این پژوهش ازنظر هدف، کاربردی و ازنظر روش، در دستۀ پژوهش‌های توصیفی-پیمایشی قرار می‌گیرد. داده‌های پژوهش از طریق توزیع لینک پرسشنامۀ آنلاین میان بیش از ۶۹۷ نفر از کاربران شبکه‌های اجتماعی در ایران و با روش نمونه‌گیری در دسترس گردآوری شد. برای تحلیل داده‌ها، از مدل‌سازی معادلات ساختاری با استفاده از نرم‌افزار ایموس بهره گرفته شد. بر اساس نتایج می‌توان گفت کاربران ایرانی با کنش‌های متفاوتی در رسانه‌های اجتماعی به اشتراک‌گذاری اطلاعات می‌پردازند و در این میان، دانش تشخیص اطلاعات نقش تعدیل‌کنندۀ اشتراک‌گذاری اطلاعات را ایفا می‌کند. یافته‌ها نشان داد کاربران ایرانی با اهدافی چون جستجوی اطلاعات، جستجوی موقعیت، ایجاد روابط اجتماعی، تعامل فرااجتماعی و ادراک گروهی، اطلاعات را در رسانه‌های اجتماعی به اشتراک می‌گذارند. همچنین، دانش تشخیص اطلاعات غیرواقعی توسط کاربران، میزان اشتراک‌گذاری اطلاعات در رسانه‌های اجتماعی را کاهش می‌دهد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Information Recognition Knowledge: A Moderator of Iranian Social Media Users' Activism

نویسندگان English

Nahid Saadat Sirat 1
Hadi Khaniki 2
1 PhD in Communication Sciences, Allameh Tabataba’i University, Tehran, Iran
2 Department of Communication Sciences, Full Professor, Allameh Tabataba’i University, Tehran, Iran
چکیده English

Predicting information sharing by social media users in Iran serves multiple objectives, including understanding their attitudes, experiences, and engagement. This study examines the information-sharing behavior of Iranian social media users and investigates the moderating role of information discernment knowledge. The primary aim of this research is to predict the factors influencing information sharing among Iranian users and to examine how information discernment knowledge moderates this behavior on social media. Users’ attitudes toward information sharing are shaped by various motivations, and understanding these factors can help develop effective strategies to optimize information sharing and enhance the quality of shared content. This study is applied in purpose and descriptive-survey in methodology. Data were collected through an online questionnaire distributed to 697 social media users in Iran using convenience sampling. Structural equation modeling (SEM) was employed to analyze the data using AMOS software. The results indicate that Iranian users engage in information sharing on social media through various actions, with information discernment knowledge playing a moderating role. Specifically, users share information with motivations such as information seeking, location seeking, social relationship building, extracommunal interaction, and collective perception. Moreover, users’ awareness and knowledge of misinformation reduce the tendency to share false information on social media.
Extended Abstract:
Introduction
In general, predicting information sharing behavior on social media requires attention to various factors. These factors can affect information sharing behavior. Among these, we can mention the cognitive ability of users, which can help them recognize the authenticity and accuracy of information. Also, the structure and design of social platforms also affect users' behavior in sharing information. In addition, strengthening information recognition knowledge in users can help improve the quality of information shared and prevent the spread of misinformation. This will lead to the expansion of awareness and positive interactions in the social media context. Information recognition can effectively moderate information sharing, especially in various contexts such as social media and user-generated content. Professional standards in information recognition can improve the quality of information among those sharing information and prevent the spread of misinformation. Therefore, the present study focused on the question of how to predict information sharing by social media users and whether information recognition knowledge can moderate it.
The theoretical framework of this study is grounded in the uses and gratifications theory, social influence theory, and social media dependency theory. The findings of this research can deepen our understanding of social media users’ engagement and provide clear strategic insights, as social media serves as a key tool in shaping and fostering user activism in contemporary society. This role emerges from the unique capabilities of social media in facilitating communication, information exchange, and enhancing the capacity to organize public opinion. The research questions address the primary objective of the study, namely predicting social media users’ engagement in information sharing and examining the moderating role of information discernment knowledge. Accordingly, the present study seeks to answer the following questions: 1. Does users’ “information seeking” lead to increased information sharing on social media? 2. Does users’ “location seeking” contribute to information sharing on social media? 3. Do users’ “social relationship building,” “extracommunal interaction,” and “collective perception” foster information sharing on social media? 4. Does users’ “information discernment knowledge” enhance information sharing on social media
Theoretical Basis and Conceptual Framework
Information sharing on social media by users means publishing and sharing content, opinions, experiences, and news on social platforms. This process greatly influences human communication and social interactions, and at the same time helps to shape collective attitudes and behaviors. This action allows users to easily convey their opinions and experiences to others. This action can help strengthen social connections and create online communities. In addition, in times of crisis, such as health or social crises, information sharing can help increase public awareness and quickly transmit vital information (Anspach & Carlson, 2018:3). Next, the research concepts are defined in the light of the theoretical framework of the research. Information sharing is derived from the theory of media use and gratification.
Information discernment knowledge refers to awareness of the functioning and characteristics of misinformation. Possessing sufficient knowledge and awareness about the nature of false information and news can help users reduce their tendency to share misleading content. Although users may not always have adequate awareness of new information or may be uncertain about its accuracy, they often still share it. Recognizing and understanding the credibility of information sources can therefore moderate the sharing of false information. When many active social media users repeatedly consume certain information and subsequently share it, this indicates that a large number of users have accepted false information as truth and are resharing it.
Methodology
The present study was conducted quantitatively using an online survey technique. The statistical population of this study is all users of the social networks Telegram, Instagram, WhatsApp, and Facebook, whose only source of receiving news and information is social media. The non-probability sampling method was used. Thus, a message was sent to the people available to the researcher on social networks stating their willingness to participate in the study and they were asked to receive and complete the questionnaire.
Advanced software (Sample Power) was used to determine the sample size for structural equation modeling. In calculating the sample size, the G power was calculated with an effect size of 0.15, alpha of 0.05, and power of 0.8 for the minimum sample size, which is 693. However, due to having a heterogeneous group and to increase generalizability, the sample size was increased to 770. From this number of questionnaires, about 697 usable responses were obtained. Data were collected from mid-June to the end of September (2023).
Findings and Conclusion
Social media are designed to facilitate social interactions. By providing communication platforms, users feel closer and more connected to each other, which can lead to stronger group perceptions. For this reason, information is quickly transmitted between users, which can lead to cultural changes. Concepts and variables such as social networking, extra-social interaction, and group perception are derived from the social media theory; they include any influence on individual feelings, thoughts, or behavior resulting from the actual presence or perceptions of others. The process of social media influence in groups can help spread misinformation. According to the social-influence theory and media addiction, to find better indicators to explain why users share information on social media, the degree of addiction to media content is significant. This is a key factor in understanding why and when audiences’ beliefs, feelings, and behaviors change; that audiences’ increasing dependence on social media for understanding the lived world and social actions is effective and meaningful. The degree of dependence on social media also depends on the information function and conflict existing in society.

کلیدواژه‌ها English

Information sharing
information discernment knowledge
social media
information seeking
social relationship building
ال­نابی، رابین و بث اُلیور، ماری (1393). فرایندها و تأثیرات رسانه‌ها. ترجمۀ: سید محمد مهدیزاده. تهران: مرکز تحقیقات صداوسیما.
بصیریان جهرمی، حسین و بردبار، ملیکا. (1395). رسانه‌های اجتماعی و مدیریت بحران: نقش تلفن‌های همراه هوشمند در کنشگری اجتماعی. فصلنامه رسانه،57-27، (1)83. https://civilica.com/doc/793277
شمس، مرتضی. (1401). ویژگی‌های اخبار در شبکه‌های اجتماعی: مطالعه موردی صفحات خبری اینستاگرام. پایان‌نامه کارشناسی ارشد. دانشکده علوم ارتباطات، دانشگاه علامه طباطبایی https://civilica.com/doc/45833659
سورین، ورنر جوزف و تانکارد، جیمز. (1401). نظریه‌های ارتباطات. ترجمۀ: علیرضا دهقان. تهران: انتشارات دانشگاه تهران.
مک‌کوایل، دنیس. (1392). درآمدی بر نظریه‌های ارتباطات. ترجمۀ: پرویز اجلالی. تهران: انتشارات مرکز مطالعات و تحقیقات رسانه‌ها.
نعمتی‌فر، نصرت. (1397). سطح سواد رسانه‌ای کاربران رسانه‌های اجتماعی. رساله دکتری. تهران: دانشگاه آزاد اسلامی، واحد تهران شمال https://civilica.com/doc/2003422.
محمد، مرادی. (1402). گونه‌شناسی کاربران رسانه‌های اجتماعی. رساله دکتری. تهران: دانشکده علوم اجتماعی، دانشگاه علامه طباطبایی https://civilica.com/doc/1858925.
 
References
Anspach, N. M., & Carlson, T. N. (2020). What to believe? Social media commentary and belief in misinformation. Political Behavior, 42(3), 697–718. https:/‌/‌doi.org/‌10.1007/‌s11109-018-9515-z
Apuke, O. D., Omar, B., Tunca, E. A., & Gever, C. V. (2024). Information overload and misinformation sharing behaviour of social media users: Testing the moderating role of cognitive ability. Journal of Information Science, 50(6), 1371–1381. https:/‌/‌doi.org/‌10.1177/‌01655515221121942
Feng, B. (2024). Gaming with health misinformation: A social capital-based study of corrective information sharing factors in social media. Frontiers in Public Health, 12, 1351820. https:/‌/‌doi.org/‌10.3389/‌fpubh.2024.1351820
Gupta, A., & Dhami, A. (2015). Measuring the impact of security, trust and privacy in information sharing: A study on social networking sites. Journal of Direct, Data and Digital Marketing Practice, 17(1), 43–53. https:/‌/‌doi.org/‌10.1057/‌dddmp.2015.32
Handarkho, Y. D. (2020). Impact of social experience on customer purchase decision in the social commerce context. Journal of Systems and Information Technology, 22(1), 47–71. https:/‌/‌doi.org/‌10.1108/‌JSIT-05-2019-0088
Hernandez, A. A., Adriano, M. C. D., Peralta, C. A. U., & Dupaya, J. P. R. E. (2024). Predicting the factors to use behavior on social media as telehealth service among generation z using structural equation modeling. 2024 IEEE 15th Control and System Graduate Research Colloquium (ICSGRC). https:/‌/‌www.semanticscholar.org/‌paper/‌08bd8ecb5ebf27fb476bf29bae6ca7f7e198bdef
Jang, S. M., & Kim, J. K. (2018). Third person effects of fake news: Fake news regulation and media literacy interventions. Computers in Human Behavior, 80, 295–302. https:/‌/‌doi.org/‌10.1016/‌j.chb.2017.11.034
Kim, K. S., Yoo-Lee, E., & Sin, S. C. J. (2011). Social media as an information source: Undergraduates’ use and evaluation behavior. Proceedings of the American Society for Information Science and Technology, 48(1), 1–3. https:/‌/‌doi.org/‌10.1002/‌meet.14504801201
Kong, H., Mahamed, M., Abdullah, Z., & Abas, W. A. (2023). Systematic literature review on driving factors of COVID-19 related fake news sharing on social media. Studies in Media and Communication, 11(7), 29–41. https:/‌/‌doi.org/‌10.11114/‌smc.v11i7.6228
Lampos, V., Moura, S., Yom-Tov, E., Cox, I. J., McKendry, R., & Edelstein, M. (2021). Tracking COVID-19 using online search. npj Digital Medicine, 4, 4. https:/‌/‌doi.org/‌10.1038/‌s41746-021-00384-w
Lee, C., Shin, J., & Hong, A. (2018). Does social media use really make people politically polarized? Direct and indirect effects of social media use on political polarization in South Korea. Telematics and Informatics, 35, 245–254. https:/‌/‌doi.org/‌10.1016/‌j.tele.2017.11.005
Li, C., & Bernoff, J. (2008). Groundswell: Winning in a world transformed by social technologies. Harvard Business Press.
López, C., Hartmann, P., & Apaolaza, V. (2019). Gratifications on social networking sites: The role of secondary school students’ individual differences in loneliness. Journal of Educational Computing Research, 57(1), 58–82. https:/‌/‌doi.org/‌10.1177/‌0735633117743917
Sijabat, L., Rantung, D. I., & Mandagi, D. W. (2023). The role of social media influencers in shaping customer brand engagement and brand perception. Jurnal Manajemen Bisnis, 9(2), 280–288. https:/‌/‌doi.org/‌10.33096/‌jmb.v9i2.459
Tandoc Jr, E. C., Lim, Z. W., & Ling, R. (2018). Defining “fake news” A typology of scholarly definitions. Digital Journalism, 6(2), 137-153. https:/‌/‌doi.org/‌10.1080/‌21670811.2017.1360143.
Thompson, N., Wang, X., Daya, P., (2019). Determinants of news sharing behavior on social media. Journal of Computer Information Systems 00 (00), 1–9. https:/‌/‌doi. org/‌10.1080/‌08874417.2019.1566803.
Torres, R.R., Gerhart, N., Negahban, A. (2018). Epistemology in the era of fake news: An exploration of information verification behaviors among social networking site users. Data Base for Advances in Information Systems, 49 (3), 78–97. https:/‌/‌doi.org/‌10.1145/‌3242734.3242740.
Tsfati, Y., & Cappella, J. N. (2017). Do people watch what they do not trust? Exploring the association between news media skepticism and exposure. Communication Research,30(5), 504-529. https:/‌/‌doi.org/‌10.1177/‌0093650207305459
Villagra, N., Reyes-Menéndez, A., Clemente-Mediavilla, J., & Semova, D. J. (2023). Using algorithms to identify social activism and climate skepticism in user-generated content on Twitter. Profesional de la Información, 32(3), e320315. https:/‌/‌doi.org/‌10.3145/‌epi.2023.may.15
Winiecki, D. J., Spezzano, F., & Underwood, C. (2023). Understanding teenagers’ real and fake news sharing on social media. In Proceedings of the 22nd Annual ACM Interaction Design and Children Conference (pp. 598–602). Association for Computing Machinery. https:/‌/‌doi.org/‌10.1145/‌3585088.3593864