Skip to content
AI News HubLIVE
Source content · Analysis pending2 min read

Real-time Chatbot Romance Scam Detection in Stage Classification

Summary

arXiv:2610.20631v1 Announce Type: new Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the study, a chatbot has developed to detect romance scam in real-time through Line Messaging API. Using the seven stage theories in the social science field, the stages of romance scam can be detected through large language model. In addition, once a romance scam is detected, the chatbot provides explanations of the stage and prevention advices through large language model. The contribution of the work provides a practical application, and can be used in real scenario for reducing the risk of romance scam.

SourcearXiv Computational LinguisticsAuthor: Yi-cheng Liu, Guan-ru Lai, Yi-cheng Lai, Lyn Chao-ling Chen
Real-time Chatbot Romance Scam Detection in Stage Classification
Report an error

The correction channel is not available yet. You can copy the article reference below for later.

Correction instructions
Read article

[Submitted on 30 Sep 2026]

Title:Real-time Chatbot Romance Scam Detection in Stage Classification

View a PDF of the paper titled Real-time Chatbot Romance Scam Detection in Stage Classification, by Yi-cheng Liu and 3 other authors

View PDF

Abstract:Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the study, a chatbot has developed to detect romance scam in real-time through Line Messaging API. Using the seven stage theories in the social science field, the stages of romance scam can be detected through large language model. In addition, once a romance scam is detected, the chatbot provides explanations of the stage and prevention advices through large language model. The contribution of the work provides a practical application, and can be used in real scenario for reducing the risk of romance scam.

Comments: Accepted in Taiwan Academic Network Conference (TANET 2026)

Subjects:

Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Multimedia (cs.MM)

Cite as: arXiv:2610.20631 [cs.CL]

(or arXiv:2610.20631v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.20631

arXiv-issued DOI via DataCite

Submission history

From: Lyn Chao-Ling Chen [view email] [v1] Wed, 30 Sep 2026 04:19:18 UTC (1,596 KB)

Full-text links:

Access Paper:

View a PDF of the paper titled Real-time Chatbot Romance Scam Detection in Stage Classification, by Yi-cheng Liu and 3 other authors

View PDF

view license

Additional Features

Audio Summary

Current browse context:

cs.CL

new | recent | 2026-10

Change to browse by:

cs cs.AI cs.MM

References & Citations

NASA ADS

Google Scholar

Semantic Scholar

Loading...

Data provided by:

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Bibliographic Explorer (What is the Explorer?)

Connected Papers Toggle

Connected Papers (What is Connected Papers?)

Litmaps Toggle

Litmaps (What is Litmaps?)

scite.ai Toggle

scite Smart Citations (What are Smart Citations?)

Code, Data, Media

Code, Data and Media Associated with this Article

alphaXiv Toggle

alphaXiv (What is alphaXiv?)

Links to Code Toggle

CatalyzeX Code Finder for Papers (What is CatalyzeX?)

DagsHub Toggle

DagsHub (What is DagsHub?)

GotitPub Toggle

Gotit.pub (What is GotitPub?)

Huggingface Toggle

Hugging Face (What is Huggingface?)

ScienceCast Toggle

ScienceCast (What is ScienceCast?)

Demos

Demos

Replicate Toggle

Replicate (What is Replicate?)

Spaces Toggle

Hugging Face Spaces (What is Spaces?)

Spaces Toggle

TXYZ.AI (What is TXYZ.AI?)

Related Papers

Recommenders and Search Tools

Link to Influence Flower

Influence Flower (What are Influence Flowers?)

Core recommender toggle

CORE Recommender (What is CORE?)

Author

Venue

Institution

Topic

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

Key points and analysis

Article intelligence

EngineersAdvanced

Key points

  • AI generation is temporarily unavailable; this entry was preserved with deterministic fallback metadata.
  • arXiv:2610.20631v1 Announce Type: new Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify…

Highlights and analysis are generated automatically and may contain errors. Check the original source.