Anis Charfi
Biographic Data
| ID | 8539436 |
|---|---|
| NAME | Anis Charfi |
| GIVEN NAMES | Anis |
| FAMILY NAME | Charfi |
| SIGNATURE | CHARFI A |
| AFFILIATIONS | Carnegie Mellon University Qatar |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Stance detection in Arabic with a multi-dialectal cross-domain stance corpus
We present a cross-domain and multi-dialectal stance corpus for Arabic, covering the major dialect groups and four Arab regions. This research provides an important language resource for automating the task of stance detection in Dialectal Arabic while carefully considering the subtle differences in stance expression across various dialects. More than 4500 sentences in our corpus have been carefully annotated according to their stance with regard…
A survey on author profiling, deception, and irony detection for the Arabic language
The possibility of knowing people traits on the basis of what they write is a field of growing interest named author profiling. To infer a user's gender, age, native language, language variety, or even when the user lies, simply by analyzing her texts, opens a wide range of possibilities from the point of view of security. In this paper, we review the state of the art about some of the main author profiling problems, as well as deception and iron…
No prominent works on this page.
A survey on author profiling, deception, and irony detection for the Arabic language
The possibility of knowing people traits on the basis of what they write is a field of growing interest named author profiling. To infer a user's gender, age, native language, language variety, or even when the user lies, simply by analyzing her texts, opens a wide range of possibilities from the point of view of security. In this paper, we review the state of the art about some of the main author profiling problems, as well as deception and iron…
Stance detection in Arabic with a multi-dialectal cross-domain stance corpus
We present a cross-domain and multi-dialectal stance corpus for Arabic, covering the major dialect groups and four Arab regions. This research provides an important language resource for automating the task of stance detection in Dialectal Arabic while carefully considering the subtle differences in stance expression across various dialects. More than 4500 sentences in our corpus have been carefully annotated according to their stance with regard…
Arabic (2 works) · Computer Science (2 works) · Linguistics (2 works) · Natural language processing (2 works) · Artificial Intelligence (1 work) · Authorship Attribution and Profiling (1 work) · Deception (1 work) · Hate Speech and Cyberbullying Detection (1 work) · Irony (1 work) · Mathematics (1 work)