Weizi Liu
Biographic Data
| ID | 4448813 |
|---|---|
| NAME | Weizi Liu |
| GIVEN NAMES | Weizi |
| FAMILY NAME | Liu |
| SIGNATURE | LIU W |
| AFFILIATIONS | Texas Christian University |
| ORCID | 0000-0003-2071-1603 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Online incivility: A systematic literature review of its definition, effects and theoretical frameworks
In this systematic review, we analyzed 67 peer-reviewed articles published between 2005 and 2025 that employ experimental designs to establish clear causality. Specifically, we focused on how online incivility is defined, operationalized, and theorized, as well as its documented effects. We found that there was a lack of theory unique to incivility; the main sites of online incivility are the comment sections of social media platforms and news we…
Rethinking the Mindfulness and Mindlessness in Media Evocation of Human-Machine Communication: A Case Study on the In-Car Robot “Nomi”
The commonly used Media Equation framework in human-machine communication research exhibits limitations when explaining human-machine relationships in the AI era, giving rise to the Media Evocation paradigm. Based on the Media Evocation framework, this study employs in-depth interviews to investigate whether interactions between humans and the in-car robot Nomi are mindful or mindless, while also examining whether these interactions prompt reflec…
Acceptance and self-protection in government, commercial, and interpersonal surveillance contexts: An exploratory study
Digital surveillance is pervasive in cyberspace, with various parties continuously monitoring online activities. The ways in which internet users perceive and respond to such surveillance across overlapping contexts warrants deeper exploration. This study delves into the acceptance of digital surveillance by internet users and their subsequent self-protective actions against it in three distinct contexts: government, commercial, and interpersonal…
Which recommendation system do you trust the most? Exploring the impact of perceived anthropomorphism on recommendation system trust, choice confidence, and information disclosure
Recommendation systems (RSs) leverage data and algorithms to generate a set of suggestions to reduce consumers’ efforts and assist their decisions. In this study, we examine how different framings of recommendations trigger people’s anthropomorphic perceptions of RSs and therefore affect users’ attitudes in an online experiment. Participants used and evaluated one of four versions of a web-based wine RS with different source framings (i.e. “recom…
“Can you tell me about yourself?” The impacts of chatbot names and communication contexts on users’ willingness to self-disclose information in human-machine conversations
Chatbots provide functional and social support in various contexts. They are often designed with humanlike features. This study examines how chatbots’ assigned names (humanlike vs. neutral vs. machinelike) and communication contexts (functional vs. social) influence users’ willingness to disclose personal information. We conducted a 3 × 2 “between-subjects” online experiment with random assignments of 299 participants. The results showed that a f…
Gender identity and influence in human-machine communication: A mixed-methods exploration
Putting the “Me” in endorsement: Understanding and conceptualizing dimensions of self-endorsement using intelligent personal assistants
Self-endorsement—depicting the “self” as an endorser of a brand—represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one’s own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommen…
Which recommendation system do you trust the most? Exploring the impact of perceived anthropomorphism on recommendation system trust, choice confidence, and information disclosure
Recommendation systems (RSs) leverage data and algorithms to generate a set of suggestions to reduce consumers’ efforts and assist their decisions. In this study, we examine how different framings of recommendations trigger people’s anthropomorphic perceptions of RSs and therefore affect users’ attitudes in an online experiment. Participants used and evaluated one of four versions of a web-based wine RS with different source framings (i.e. “recom…
Putting the “Me” in endorsement: Understanding and conceptualizing dimensions of self-endorsement using intelligent personal assistants
Self-endorsement—depicting the “self” as an endorser of a brand—represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one’s own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommen…
Putting the “Me” in endorsement: Understanding and conceptualizing dimensions of self-endorsement using intelligent personal assistants
Self-endorsement—depicting the “self” as an endorser of a brand—represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one’s own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommen…
“Can you tell me about yourself?” The impacts of chatbot names and communication contexts on users’ willingness to self-disclose information in human-machine conversations
Chatbots provide functional and social support in various contexts. They are often designed with humanlike features. This study examines how chatbots’ assigned names (humanlike vs. neutral vs. machinelike) and communication contexts (functional vs. social) influence users’ willingness to disclose personal information. We conducted a 3 × 2 “between-subjects” online experiment with random assignments of 299 participants. The results showed that a f…
Gender identity and influence in human-machine communication: A mixed-methods exploration
Acceptance and self-protection in government, commercial, and interpersonal surveillance contexts: An exploratory study
Digital surveillance is pervasive in cyberspace, with various parties continuously monitoring online activities. The ways in which internet users perceive and respond to such surveillance across overlapping contexts warrants deeper exploration. This study delves into the acceptance of digital surveillance by internet users and their subsequent self-protective actions against it in three distinct contexts: government, commercial, and interpersonal…
Which recommendation system do you trust the most? Exploring the impact of perceived anthropomorphism on recommendation system trust, choice confidence, and information disclosure
Recommendation systems (RSs) leverage data and algorithms to generate a set of suggestions to reduce consumers’ efforts and assist their decisions. In this study, we examine how different framings of recommendations trigger people’s anthropomorphic perceptions of RSs and therefore affect users’ attitudes in an online experiment. Participants used and evaluated one of four versions of a web-based wine RS with different source framings (i.e. “recom…
Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Online incivility: A systematic literature review of its definition, effects and theoretical frameworks
In this systematic review, we analyzed 67 peer-reviewed articles published between 2005 and 2025 that employ experimental designs to establish clear causality. Specifically, we focused on how online incivility is defined, operationalized, and theorized, as well as its documented effects. We found that there was a lack of theory unique to incivility; the main sites of online incivility are the comment sections of social media platforms and news we…
Rethinking the Mindfulness and Mindlessness in Media Evocation of Human-Machine Communication: A Case Study on the In-Car Robot “Nomi”
The commonly used Media Equation framework in human-machine communication research exhibits limitations when explaining human-machine relationships in the AI era, giving rise to the Media Evocation paradigm. Based on the Media Evocation framework, this study employs in-depth interviews to investigate whether interactions between humans and the in-car robot Nomi are mindful or mindless, while also examining whether these interactions prompt reflec…
Psychology (5 works) · Social Psychology (4 works) · Business (3 works) · Computer Science (3 works) · Internet privacy (3 works) · World Wide Web (3 works) · AI in Service Interactions (2 works) · Cybercrime and Law Enforcement Studies (2 works) · Digital Marketing and Social Media (2 works) · Privacy, Security, and Data Protection (2 works)