AI Intervention for social exclusion: the emotional regulation function and basic need satisfaction mechanism of chatbots

This study investigates how chatbot interaction affects the basic needs of individuals experiencing social exclusion, the mediating role of positive emotions, and the optimal level of linguistic anthropomorphism in chatbots. This study was conducted through three progressive experiments. Study 1 employed the Cyberball paradigm to induce social exclusion, and the results showed that excluded individuals had a significantly higher willingness to use chatbots.

Study 2 combined the O-Cam paradigm, physiological indicators, and scale measurements, confirming that chatbot use could significantly enhance basic needs such as belongingness and self-esteem, as well as positive emotions, while reducing negative emotions. Among these relationships, positive emotions played a full mediating role. Study 3 set up three groups with low, medium, and high levels of linguistic anthropomorphism.

The results indicated that chatbots with a medium level of anthropomorphism achieved the optimal effects in improving basic needs, enhancing positive emotions, and reducing negative emotions. Collectively, these findings indicate that chatbots can serve as effective intervention tools for social exclusion, with their mechanisms of action related to the mediation of positive emotions and moderate anthropomorphism. This research provides theoretical and practical implications for relevant psychological interventions.

This work was supported by the General Program of Basic Scientific Research of the Department of Education of Liaoning Province (LJ212410165052) and the National Natural Science Foundation of China (62476046). The views expressed in this study do not necessarily reflect those of the funding agencies. The funders had no role in the study design and implementation, data collection, management, analysis, and interpretation; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.

College of Psychology, Liaoning Normal University, Dalian, China SEAC Key Laboratory of Big Data Applied Technolog, Dalian Minzu University, Dalian, China The authors declare no competing interests. This study was approved by the Experimental Ethics Committee of Liaoning Normal University, with the ethical review number: LL2025014, and the approval date [Jan/8/2025]. All research procedures were performed in strict accordance with the Declaration of Helsinki and other relevant ethical guidelines and regulations for research involving human participants.

The ethical approval letter (in English) is included in the cover letter as supporting information. Informed consent was obtained in writing from all human participants prior to their participation in the study. All participants voluntarily participated in this experiment, were fully informed of the experiment before the formal experiment, and signed the informed consent form.