Hamed Babaei Giglou

Hamed Babaei Giglou
University of Tabriz · Department of Computer Science

Master of Science

About

10
Publications
512
Reads
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16
Citations
Citations since 2016
10 Research Items
16 Citations
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201620172018201920202021202202468
201620172018201920202021202202468
Introduction
I am an M.Sc. student of soft computing and AI. My research Interest includes Machine Learning, Deep Learning, and Natural Language Processing.

Publications

Publications (10)
Conference Paper
Full-text available
The intended sarcasm cannot be understood until the listener observes that the text’s literal meaning violates truthfulness. Consequently, words and meanings play an essential role in specifying sarcasm. Enriched feature extraction techniques were proposed to capture both words and meanings in the contexts. Due to the overlapping features in sarcas...
Conference Paper
Full-text available
Figurative language is using words in a way that deviates from the conventional order and meaning in order to ask the reader or listener to understand the meaning by virtue of its relation to some other meaning or concept. It is a rapidly growing area in Natural Language Processing, including the processing of irony, sarcasm, as well as other figur...
Preprint
Full-text available
The Persian language is an inflectional SOV language. This fact makes Persian a more uncertain language. However, using techniques such as ZWNJ recognition, punctuation restoration, and Persian Ezafe construction will lead us to a more understandable and precise language. In most of the works in Persian, these techniques are addressed individually....
Conference Paper
Full-text available
Hate Speech (HS) in social media such as Twitter is a complex phenomenon that attracted a significant body of research in the NLP. HS Spreaders (haters) aim to spread HS via social media. In this task, we aim to identify such haters. On one hand, our proposed class-dependent LDSE representation is fed to a linear SVM classifier to identify the hate...
Preprint
Full-text available
Toxic Spans Detection(TSD) task is defined as highlighting spans that make a text toxic. Many works have been done to classify a given comment or document as toxic or non-toxic. However, none of those proposed models work at the token level. In this paper, we propose a self-attention-based bidirectional gated recurrent unit(BiGRU) with a multi-embe...
Article
Full-text available
Fake news detection on social medial has attracted a huge body of research as one of the most important tasks of social analysis in recent years. In this task, given a Twitter feed, the goal is to identify fake/real news authors or spreaders. We assume fake news authors mostly like to play with the semantic aspect of news rather than trying to add...
Conference Paper
Full-text available
Author Attribution (AA) as one of the most important tasks of authorship analysis attracted huge body of research in recent years. In this task, given a document, the goal is to identify its author from a set of known authors and samples of their writings. In PAN 2019 shared tasks, the AA task is expanded in two ways. First, by having documents wri...
Conference Paper
Full-text available
Author verification algorithms mainly rely on learning statistical fingerprints of authors. In the other hand, most of the previous algorithms in author masking try to apply changes to the original texts blindly without considering those fingerprints. In this paper, we propose an approach that learns author's fingerprints and uses them to apply dir...
Article
Full-text available
Author Profiling is one of the most important tasks in authorship analysis. In PAN 2019 shared tasks, the gender identification of the author is the main focus. Compared to the previous year the author profiling task is expended by having documents written by bots. In order to tackle this new challenge we propose a two phase approach. In the first...

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Projects

Projects (2)
Archived project
Given a Twitter feed, determine whether its author is keen to be a spreader of fake news