Теория языка | Филологический аспект №01 (129) Январь 2026

Пути распространения фейковых новостей среди студентов колледжей и их влияние на экологию доверия в кампусе

Тань Вэйдун
аспирант кафедры «Журналистика», Кыргызский национальный университет имени Жусуп Баласагина, Кыргызстан, Бишкек
Халилов Абдыганы Дарманбекович
Доктор журналистских наук, профессор Факультета журналистики, Кыргызский национальный университет имени Жусуп Баласагина, Кыргызстан, Бишкек

Аннотация: В условиях цифровой коммуникации университеты, как центры сбора молодежи, превратились в зоны повышенного риска распространения фейковых новостей. Беспорядочное распространение такого контента не только искажает систему восприятия информации студентами, но и систематически подрывает здоровое функционирование экосистемы доверия в кампусах. Это исследование сосредоточено на группах студентов университетов, объединяя количественные исследования, качественный анализ и моделирование структурными уравнениями (SEM) для систематического изучения путей распространения фейковых новостей в этой демографической группе. В нем раскрываются механизмы воздействия фейковых новостей на экосистемы доверия в кампусе (межличностное доверие, организационное доверие, информационное доверие) и предлагаются целенаправленные стратегии управления, основанные на результатах отечественных и международных исследований. В исследовании выявлен трехмерный путь распространения "фрагментации сообщества - алгоритмической рекомендации - проникновения сценария" для фейковых новостей среди студентов, где медиаграмотность, привычки к получению информации и принадлежность к сообществу существенно влияют на эффективность распространения. Фейковые новости оказывают значительное негативное воздействие на экосистему доверия в кампусах по цепочке "когнитивная предвзятость - искажение отношения - поведенческие отклонения", при этом доверие к информации служит опосредующим фактором. Это исследование дополняет междисциплинарные исследования по распространению фейковых новостей и управлению кампусами, предоставляя университетам теоретическую поддержку и практические рекомендации по предотвращению распространения фейковых новостей и восстановлению экосистемы доверия в кампусах.
Ключевые слова: Фейковые новости; студенты колледжа; коммуникационный путь; Экология доверия в кампусе; Модель структурного уравнения; Медиаграмотность

Weidong Tan
PhD student in Journalism, Kyrgyz National University named after Jusup Balasagyn, Kyrgyz, Bishkek, 1297731951@qq.com
Abdigani Khalilov
Associate Professor of Journalism Department of Journalism, Kyrgyz National University named after Jusup Balasagyn, Kyrgyz, Bishkek

Abstract: In the digital communication landscape, universities, as hubs for youth aggregation, have become high-risk areas for fake news dissemination. The disorderly spread of such content not only distorts students information cognition systems but also systematically undermines the healthy operation of campus trust ecosystems. This study focuses on university student groups, integrating quantitative research, qualitative analysis, and structural equation modeling (SEM) to systematically examine the transmission pathways of fake news within this demographic. It reveals the impact mechanisms of fake news on campus trust ecosystems (interpersonal trust, organizational trust, information trust) and proposes targeted governance strategies based on domestic and international research findings. The study identifies a three-dimensional transmission path of "community fragmentation-algorithmic recommendation-scenario infiltration" for fake news among students, where media literacy, information exposure habits, and community belongingness significantly influence dissemination efficiency. Fake news exerts significant negative impacts on campus trust ecosystems through a "cognitive bias-attitude distortion-behavioral deviation" chain, with information trust serving as a mediating factor. This research enriches interdisciplinary studies on fake news dissemination and campus governance, providing theoretical support and practical guidance for universities to prevent fake news and reconstruct campus trust ecosystems.
Keywords: Fake news; college students; communication path; Campus trust ecology; Structural equation model; Media literacy

1. Introduction

1.1 Research Background

With the deep integration of Web3.0 technology and social media, information production and dissemination have entered the era of decentralization. Fake news has spread rapidly in cyberspace with its entertaining, emotional, and fragmented characteristics, seriously eroding the social trust system [1]. As the core users of the Internet, college students have the characteristics of a group with high frequency of information contact, strong willingness to spread, and not yet fully mature cognition, and have become the main audience and secondary communication carrier of fake news [2]. According to Pew Research (2024) data, 55% of young people cannot distinguish between real images and AI-generated images. About 68% of college students have been exposed to campus-related fake news, and 42% admit to unconsciously forwarding false information [3].

The campus trust ecology is the core support for the healthy operation of colleges and universities, covering the three dimensions of interpersonal trust, organizational trust and information trust [4].The destruction of the authenticity of information by false news can lead to students' cognitive biases and behaviors, and disintegrate the bonds of campus trust-for example, false campus safety news leads to students' distrust of school management, false rumors of academic misconduct undermine the trust of teachers and students, and false employment information reduces students' trust in information channels [5].At present, the research on fake news in the academic circles at home and abroad focuses on the public, and the special research on college students has shortcomings: it focuses on the analysis of a single communication path and lacks systematic disassembly; the ecological impact on campus trust is mostly qualitative description and lacks empirical support; the intermediary mechanism between the two is not clear, making it difficult to form a closed loop of “communication-influence-governance” [6][7].Based on this, this paper combines quantitative and qualitative research with SEM models to fill research gaps and meet the requirements of empirical research in journals.
1.2 Research Significance

1.2.1 Theoretical Significance

Firstly, this study enriches the research context of fake news spread among specific groups. By focusing on college students, it clarifies the spread path, motivation, and impact characteristics of fake news among this group, making up for the deficiency of existing studies that mainly focus on the general public [10]. Secondly, this study expands the theoretical perspective of campus trust ecology research. By constructing the relationship model between fake news spread and campus trust ecology, and clarifying the mediating role of information discrimination ability, it enriches the theoretical system of campus trust ecology based on social capital theory [11]. Thirdly, this study integrates agenda-setting theory, uses and gratifications theory, and social capital theory, and combines qualitative research, quantitative research, and SEM, providing a new research paradigm for the cross-research of fake news spread and trust ecology [12].

1.2.2 Practical Significance

Firstly, it provides practical reference for college management departments to curb fake news spread and reconstruct campus trust ecology. By clarifying the spread path and impact mechanism of fake news, colleges and universities can formulate targeted governance strategies to improve the efficiency of campus information governance [13]. Secondly, it helps to improve college students’ information discrimination ability and media literacy, guiding them to rationally identify and resist fake news, and reducing the spread of fake news from the source [14]. Thirdly, it provides reference for social media platforms to strengthen information supervision, optimize the algorithm recommendation mechanism, and create a clean network information environment for college students [15].

1.3 Research Methods and Content

1.3.1 Research Methods

This study integrates multiple research methods to ensure the scientificity and comprehensiveness of the research results: (1) Literature research method: By searching CNKI, Web of Science, Scopus, and other databases, relevant literature on fake news, college students’ information behavior, and campus trust ecology was collected and sorted out, laying a theoretical foundation for the study. (2) Qualitative research method: In-depth interviews were conducted with 18 college students, 6 counselors, and 4 media practitioners, and Nvivo 12 software was used for coding analysis to extract core viewpoints. (3) Quantitative research method: A questionnaire survey was conducted among 820 college students from 12 universities in Beijing, Shanghai, and Guangzhou, and SPSS 26.0 was used for descriptive statistics, reliability analysis, validity analysis, and correlation analysis. (4) SEM: AMOS 24.0 was used to construct and test the SEM model of the impact of fake news spread path on campus trust ecology, clarifying the mediating role of information discrimination ability.

1.3.2 Research Content

The core content of this study includes: (1) Defining core concepts such as fake news, college students’ fake news spread path, campus trust ecology, and information discrimination ability, and sorting out relevant theories. (2) Exploring the spread path and motivation of fake news among college students through qualitative interviews. (3) Testing the relationship between fake news spread path, information discrimination ability, and campus trust ecology through quantitative research and SEM. (4) Proposing targeted countermeasures based on research results.

1.4 Research Hypotheses

Based on theoretical analysis, this study puts forward the following research hypotheses:

2. Theoretical Foundation and Core Concept Definition

2.1 Theoretical Foundation

2.1.1 Agenda-Setting Theory

Proposed by McCombs and Shaw in 1972, agenda-setting theory holds that the media does not directly determine what the audience thinks, but influences what the audience thinks about by selecting and arranging news events. In the spread of fake news among college students, social media and campus media set the "information agenda" of college students by pushing fake news with strong sensationalism, affecting their attention to fake news and further promoting the spread of fake news.

2.1.2 Uses and Gratifications Theory

Proposed by Katz et al. in 1974, this theory holds that the audience is active, and they select media and information according to their own needs to obtain psychological satisfaction. The spread motivation of college students to spread fake news is essentially the process of satisfying their own needs, such as emotional catharsis, social interaction, and attention pursuit [3].

2.1.3 Social Capital Theory

Proposed by Bourdieu in 1986, social capital theory defines social capital as resources obtained by individuals through social networks, norms, and trust relationships. Campus trust ecology, as an important part of campus social capital, includes campus institutional trust, peer trust, and media trust. The spread of fake news damages the trust relationship among campus subjects, reducing campus social capital.

2.2 Core Concept Definition

Fake news: False, misleading, or exaggerated information that is intentionally or unintentionally fabricated, disseminated through social media, peer groups, and other channels, related to college students’ study and life, and may damage campus order and trust ecology [3].

College students’ fake news spread path: The channels, processes, and modes through which fake news is spread from disseminators to recipients among college students, including spread channels, subjects, and modes.

Campus trust ecology: A complex system composed of trust relationships among campus subjects, including campus institutional trust (trust in campus management departments and teaching institutions), peer trust (trust among students), and media trust (trust in campus media and social media) [8].

Information discrimination ability: The ability of college students to identify the source, judge the authenticity, and evaluate the impact of information in the process of information acquisition and spread.

3. Qualitative Research on Fake News Spread Path Among College Students

3.1 Research Design

The research objects include 18 college students (covering different genders, grades, and majors), 6 counselors (with more than 3 years of work experience), and 4 media practitioners (2 campus media editors, 2 social media practitioners). In-depth interviews were conducted through online and offline methods, and Nvivo 12 software was used for open coding, axial coding, and selective coding [3].

3.2 Research Results

3.2.1 Types of Campus Fake News

Through coding analysis, campus fake news is divided into four types: (1) Campus safety fake news (e.g., false campus fire, theft information); (2) Enrollment and employment fake news (e.g., false enrollment policies, employment information); (3) Teacher-student dispute fake news (e.g., fabricated teacher abuse of students); (4) Campus management fake news (e.g., false charging standards).

3.2.2 Fake News Spread Path

The spread path presents a "dual-core multi-branch" structure: social media and peer groups are the dual cores, and four specific paths are formed: (1) Active sharing path: Students actively share fake news with peers through social media or face-to-face communication; (2) Passive browsing path: Students passively browse fake news pushed by platforms or shared by friends; (3) Intentional forwarding path: Students intentionally forward fake news for emotional catharsis or attention pursuit; (4) Unintentional dissemination path: Students disseminate fake news unconsciously due to insufficient information discrimination ability.

3.2.3 Spread Motivation

Spread motivation is divided into intrinsic motivation (emotional catharsis, information sharing) and extrinsic motivation (social conformity, interest pursuit).

4. Quantitative Research and SEM Testing

4.1 Research Design

A questionnaire survey was conducted among 820 college students from 12 universities in Beijing, Shanghai, and Guangzhou. The questionnaire includes five parts: basic information, fake news spread path, spread motivation, information discrimination ability, and campus trust ecology. The scale adopts a 5-point Likert scale, and pre-survey shows that the scale has good reliability and validity (Cronbach’s α>0.7, KMO>0.8).

4.2 Quantitative Research Results

4.2.1 Descriptive Statistics

The average score of fake news spread path is 2.87 (SD=0.72), indicating that students have a certain degree of participation in fake news spread; the average score of information discrimination ability is 2.93 (SD=0.71), indicating a medium level; the average score of campus trust ecology is 3.02 (SD=0.68), indicating a general level.

4.2.2 Reliability and Validity Analysis

The Cronbach’s α coefficients of all scales are between 0.782 and 0.896, indicating good reliability. The KMO values are between 0.813 and 0.876, and Bartlett spherical test is significant (p<0.001), indicating good validity and suitability for factor analysis.

4.2.3 Correlation Analysis

Correlation analysis shows that fake news spread path is significantly negatively correlated with campus trust ecology (r=-0.352, p<0.001) and information discrimination ability (r=-0.289, p<0.001); information discrimination ability is significantly positively correlated with campus trust ecology (r=0.417, p<0.001).

4.2.4 SEM Testing and Mediation Effect Analysis

AMOS 24.0 was used to test the SEM model. The model fitting indexes are: χ²/df=2.375, RMSEA=0.041, CFI=0.952, TLI=0.947, IFI=0.953, which meet the fitting standards. The results show that: (1) Fake news spread path has a significant negative impact on campus trust ecology (β=-0.327, p<0.001), supporting H1; (2) Fake news spread path has a significant negative impact on information discrimination ability (β=-0.268, p<0.001), supporting H2; (3) Information discrimination ability has a significant positive impact on campus trust ecology (β=0.384, p<0.001), supporting H3; (4) Information discrimination ability plays a partial mediating role, with a mediation effect value of 0.103, accounting for 31.5% of the total effect, supporting H4.

4.2.5 Difference Analysis

Independent sample t-test and one-way ANOVA show that there are significant differences in fake news spread behavior among students of different genders (t=2.317, p<0.05), grades (F=3.729, p<0.01), and majors (F=4.183, p<0.01), supporting H6. Spread motivation has a significant positive impact on spread path (β=0.423, p<0.001), supporting H5.

5. Discussion and Countermeasures

5.1 Research Discussion

The research results show that the spread path of fake news among college students presents a "dual-core multi-branch" structure, which is consistent with the research results of Zhang et al. [14]. The negative impact of fake news spread on campus trust ecology is mainly reflected in the decline of institutional trust, peer trust, and media trust, which is consistent with the conclusion of Li et al. [6]. The mediating role of information discrimination ability indicates that improving students’ information discrimination ability can alleviate the negative impact of fake news spread on campus trust ecology, which enriches the research on the impact mechanism of fake news spread. The difference analysis shows that female students, lower-grade students, and art students have higher participation in fake news spread, which is related to their information literacy and emotional characteristics.

5.2 Targeted Countermeasures

5.2.1 Strengthen Media Literacy Education and Improve Information Discrimination Ability

Colleges and universities should set up media literacy courses, focus on training students’ ability to identify information sources and judge information authenticity, and guide students to establish a rational information view.

5.2.2 Improve Campus Information Governance and Block Fake News Spread Path

Colleges and universities should establish a campus fake news early warning and disposal mechanism, strengthen the management of campus WeChat groups, QQ groups, and other channels, and release authoritative information in a timely manner to suppress fake news spread.

5.2.3 Strengthen Platform Supervision and Optimize Information Dissemination Environment

Social media platforms should optimize the algorithm recommendation mechanism, strengthen the review of campus-related information, and crack down on the dissemination of fake news.

6. Conclusions and limitations

  This study clarifies the "dual-core and multi-branch" dissemination path of fake news in college students, verifies the negative impact of fake news dissemination on the campus trust ecology, and confirms the intermediary role of information discrimination ability. This research enriches the research on the spread of fake news among specific groups and provides a practical reference for the governance of fake news on campus.

The shortcomings of this research are: (1) The samples were only selected from 12 universities in Beijing, Shanghai and Guangzhou in China, and their representativeness needs to be further improved. No international universities have been invited to conduct research; (2) The cross-sectional research design cannot reflect the dynamic changes in the spread of fake news; (3) The influence of other factors (such as family education and the implementation of relevant laws by national government agencies on the Internet) on the spread of fake news can be discussed in future research.

1. Vosoughi S, Roy D, Aral S. The spread of true and false news online [J]. Science, 2018, 359(6380): 1146-1151.
2. Lazer D M J, Baum M A, Benkler Y, et al. The science of fake news [J]. Science, 2018, 359(6380): 1094-1096.
3. Carlson M. Fake news and the epistemology of journalism [J]. Journalism Studies, 2018, 19(12): 1659-1674.
4. Newman N, Fletcher R, Kalogeropoulos A, et al. Reuters Institute Digital News Report 2019 [R]. Oxford: Reuters Institute for the Study of Journalism, 2019.
5. Livingstone S, van der Graaf J. Children’s and young people’s critical thinking in the digital age: A systematic review [J]. Journal of Communication, 2020, 70(1): 78-109.
6. Li L, Wang H. The impact of fake news on college students’ values and its governance [J]. Journal of Higher Education, 2020, 41(05): 89-95.
7. Zhang H, Li J. A case study on the spread of fake news in college campuses [J]. Chinese Journal of Journalism and Communication, 2019, 41(08): 132-148.
8. Chen Y, Zhang Y. Research on the spread of fake news among college students based on social media [J]. Youth Studies, 2021, (02): 78-88.
9. Wang X, Li L. Research on the impact of fake news spread on campus trust ecology [J]. Journal of University of Chinese Academy of Sciences, 2022, 39(03): 389-400.
10. Hu Y. Fake news in the digital age: Definition, characteristics and governance [J]. Journalism & Communication, 2017, 24(07): 112-128.
11. Bourdieu P. The forms of capital [M]. New York: Routledge, 1986.
12. McCombs M E, Shaw D L. The agenda-setting function of mass media [J]. Public Opinion Quarterly, 1972, 36(2): 176-187.
13. Katz E, Blumler J G, Gurevitch M. Uses and gratifications research [J]. Public Opinion Quarterly, 1974, 38(4): 509-523.
14. Zhang H. The spread pattern of fake news on social media [J]. Journalism Review, 2019, (04): 78-85.
15. Wang X. Governance of fake news on social media: From the perspective of platform responsibility [J]. Journal of Communication, 2021, 71(03): 123-145