Skip to main content

Not your ordinary catfishing story: The role of cancel culture behind the hashtag #SamMoralesisOver

Bonne Cañal ; Ira Capuyan ; Hannah del Pilar ; Myril Eloise Enolpe ; Susan Loseo (2022) — Plaridel 19(1), 91–113

Citation activity

Total citations · Google Scholar
Unavailable
Average per calendar year
Citation count unavailable

Counts reflect Google Scholar’s coverage and do not measure research quality. Source, calculation and limitations

What do these research terms mean?
Preprint
A manuscript shared before formal peer review and publication. Check whether a later published version is available.
Dataset
A collection of data or examples for others to inspect or reuse. It can appear in Library search and topic mapping, but RSRC does not use dataset records as evidence in Research Insights.
Dissertation or thesis
Research submitted for an academic degree. This describes its format, not its reliability.
Journal article
An article published in a journal. This label alone does not establish peer review, study quality, or how well the findings apply elsewhere.
Qualitative research
Examines experiences, meanings, or processes, often through interviews or observations. It can explain how something happens without estimating how common it is.
Quantitative research
Uses numerical measurements to describe patterns or test relationships. A relationship between two measurements does not by itself show that one causes the other.
Systematic review
Uses a planned, documented method to find and assess research addressing a question. Its conclusions still depend on the included studies and what the search covered.
Meta-analysis
Statistically combines results from multiple studies. Combining studies does not remove weaknesses in their design or make unlike populations interchangeable.
Not classified
This record has no recognized label in this filter. It does not mean the publication used no method, or that no research exists.

Definitions draw on DataCite resource types; Cochrane review methods; NLM: association and causation. RSRC’s dataset and classification rules are explained in our methodology.

Citation tools


              
              

Transparency

Evidence and review status

This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

Source basis
Downloaded PDF
Source updates
No notice found at last check
AI-generated page content
Yes
Automated checks
Passed
Administrative approval
Yes
Human content review
Not recorded
Subject-matter-expert review
Not recorded
How this was prepared
Source basis

RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.

  • PDF added to RSRC:
Source updates

No incoming update notice was found in the dated Crossref response. Coverage is incomplete, particularly for corrections and expressions of concern; this is not a guarantee that the source is valid or unchanged.

  • Last source-status attempt:
AI-generated page content

AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.

  • Document analysis recorded:
  • Synopsis generation recorded:
  • Page record updated:
Automated checks

The current, source-bound synopsis passed the recorded versioned publication checks.

  • Checks completed:
View passed checks (3)
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
  • Numerical claims checked against the available source text
  • English-source lexical grounding check
Administrative approval

An authenticated administrator approved the bibliographic record for public Library display. This is not a review of every research claim.

  • Approved for public display:
Human content review

No human review is recorded for the AI-generated content displayed on this page.

Subject-matter-expert review

RSRC has not recorded review of this content by a subject-matter or methods expert.

Review-state definitions
Found a possible error? Request a correction.

Synopsis

This study explores how the online phenomenon of cancel culture operated around the hashtag #SamMoralesIsOver and how it affected LGBTQ+ catfishing victims’ willingness to speak out. Grounded in a phenomenological approach, the researchers conducted focus group discussions with eight LGBTQ+ individuals who either experienced catfishing or engaged with the hashtag by retweeting or commenting. They apply three theoretical lenses—Convergence Culture, the Spiral of Silence, and Empowerment—to understand how online participation translates into voice, solidarity, and perceived accountability. The findings show that participants generally defined cancel culture as a collective online effort to condemn offensive acts or beliefs and demand accountability, with Twitter identified as the most convenient platform for mobilization. The decision to speak out or participate was shaped by factors such as relatability to the victim, the aim of raising awareness, and the perpetrator’s stated motive for the catfishing. The study attributes a coordinating role to social networks in magnifying calls for justice, illustrating how convergence culture enables victims to act as both consumers and producers of online content, thereby challenging the Spiral of Silence by providing a space to share experiences and support one another. Participants also weighed the benefits and risks: cancel culture can raise awareness and deter future harm, yet it can also invite privacy invasions, public shaming, and hateful backlash toward both the perpetrator and the community. The authors conclude that cancel culture can empower marginalized groups online by amplifying voices and mobilizing allies, but it requires careful, critical engagement to avoid harmful oversimplifications or retaliation that undermines the broader goal of justice and education.

Identified Gaps

The paper identifies limited research on cancel culture, especially beyond case studies of public figures and businesses. It also states that little information is available on issues specifically concerning LGBTQ+ communities. The authors call for research on how cancel culture mobilizes people and raises awareness, as well as first-hand experiences in other catfishing cases.

Methods

This qualitative phenomenological study used a focus group discussion with eight convenience-sampled participants. Participants met at least two criteria: LGBTQ+ membership, catfishing victimization, and participation in the #SamMoralesIsOver Twitter issue. Responses were interpreted through Convergence Culture, Spiral of Silence, and Empowerment theories to examine definitions of cancel culture, platform use, participation, and speaking out.

Limitations

The study was narrowly scoped to the Sam Morales case and LGBTQ+ community. It used a small, non-probability convenience sample of eight people, of whom only three reported catfishing victimization. Most participants engaged through liking, retweeting, or sharing rather than publicly disclosing their own experiences. Findings therefore provide contextual perceptions of one Twitter-centered cancellation event rather than broadly generalizable evidence about catfishing or cancel culture.

Future Work

Use Co-cultural Theory; conduct in-depth interviews with victims from other catfishing cases; examine cancel-culture movements involving other marginalized groups; test whether the study's definition of cancel culture applies across movements and purposes; investigate effects of cancellation on cancelled individuals, including employment, popularity, and whether established status changes these effects.

See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.