Automatic profile recognition of authors on social media based on hybrid approach

Ellouze, Mourad; Mechti, Seifeddine; Belguith, Lamia Hadrich

doi:10.1016/j.procs.2020.09.107

Cited by 11 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For this reason, there are a lot of researchers who have turned to statistical approaches (Pramodh and Vijayalata 2016 ; Ellouze et al. 2020 ) rather than classical machine learning techniques (Stankevich et al. 2018 ; Mbarek et al.…”

Section: Related Workmentioning

confidence: 99%

A hybrid approach for the detection and monitoring of people having personality disorders on social networks

Ellouze

Belguith

2022

Soc. Netw. Anal. Min.

Self Cite

View full text Add to dashboard Cite

Research in the medical field does not stop evolving. This evolution obliges doctors to be up-to-date in order to well manage every situation that may occur with their patients. However, the medical field is very sensitive and requires a great deal of precision, all of that poses a major problem. Consequently, there is a recourse to computer science, to resolve all of these issues. In this context, we propose in this paper an architecture, taking advantage of artificial intelligence (AI) and text mining techniques to: (i) identify individuals with personality disorder from their textual production on social networks by classifying their set of tweets into distinct classes representing respectively the presence, the category and the type of the disease and (ii) guarantee personalized monitoring by filtering inappropriate tweets according to patient’s circumstance. The first phase was achieved by taking advantage of a deep neuronal approach that benefits of: (i) CNN layers for features extraction from the textual part, (ii) two LSTM layers to preserve long-term dependencies between different lexical units, (iii) SVM classifier to detect the sick person using the dependency links found from the previous layer. The second phase was accomplished by applying a hybrid approach that combined linguistic and statistical techniques in order to filter inappropriate tweets according to the state of each patient. Following the evaluation of our approach, we acquire an F-measure rate equivalent to 84% for the detection of personality disorder, 64% for the detection of the type of disease and 70% for the task of filtering inappropriate content. The obtained results are motivating and may encourage researchers to improve them in view of the interest and the importance of this research axis.

show abstract

Section: Related Workmentioning

confidence: 99%

A hybrid approach for the detection and monitoring of people having personality disorders on social networks

Ellouze

Belguith

2022

Soc. Netw. Anal. Min.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, we have no consensus on the selection of features in Table 1 and cannot be limited to the above mentioned features. User's digital footprint in social networks [60], users' attention on the image [61], statistical measures [62], and other accessible features are all meaningful to cyber personality prediction. As the saying goes, 'Birds of a feather flock together.'…”

Section: Remaining Problemsmentioning

confidence: 99%

How to respond to emerging threats of cyberspace security via social engineering? A novel paradigm to solve cyberspace security issues

Lin¹

2022

Preprint

View full text Add to dashboard Cite

Cybersecurity researchers always ignore the “people” behind the issues when dealing with cyberspace security issues. The human and technological aspects of cyberspace security must be simultaneously addressed to enable a secure cyber environment. Social engineering is a discipline whose research object is people, and the combination of social engineering and cyberspace security can provide new solution ideas for lots of cyberspace security issues. This paper attempts to answer the question —— “How to solve cyberspace security issues via social engineering?” We briefly review existing frameworks for social engineering attacks and pro?pose a novel, recursive, and iterative framework for social engineering attacks in cyberspace. The existing research achievements of combination of social engineering and cyberspace security were reviewed in the order of cyber personality, hacker psychology, human flesh search, and social engineering defense. To answer this question, we summarized four “guidelines” for using social engineering. Finally, we look ahead, give our thoughts, and discuss answers of the question and future research. It is aimed at getting more researchers of cyberspace security and social science to pay attention to this field.

show abstract

“…The extension of the existing techniques may in several cases be a useful solution, which consists in granting to an existing solution new functionalities. In this context, [12] have proposed an approach which makes it possible to integrate the notion of fuzzy logic into the functioning of traditional learning algorithms to detect the profiles of social network users (gender, age, personality traits).…”

Section: Related Workmentioning

confidence: 99%

A deep learning approach for detecting the behavior of people having personality disorders towards Covid-19 from Twitter

Ellouze¹,

Mechti²,

Krichen³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

This paper proposes an architecture taking advantage of artificial intelligence and text mining techniques in order to: (i) detect paranoid people by classifying their set of tweets into two classes (Paranoid/not-Paranoid), (ii) ensure the surveillance of these people by classifying their tweets about Covid-19 into two classes (person with normal behavior, person with inappropriate behavior). These objectives are achieved using an approach that takes advantage of different information related to the textual part, user and tweets for features selection task and deep neural network for the classification task. We obtained as an F-score rate 70% for the detection of paranoid people and 73% for the detection of the behavior of these people towards Covid-19. The obtained results are motivating and encouraging researchers to improve them given the interest and the importance of this research axis.

show abstract

Automatic profile recognition of authors on social media based on hybrid approach

Cited by 11 publications

References 6 publications

A hybrid approach for the detection and monitoring of people having personality disorders on social networks

A hybrid approach for the detection and monitoring of people having personality disorders on social networks

How to respond to emerging threats of cyberspace security via social engineering? A novel paradigm to solve cyberspace security issues

A deep learning approach for detecting the behavior of people having personality disorders towards Covid-19 from Twitter

Contact Info

Product

Resources

About