Dima Kagan
Biographic Data
| ID | 3925054 |
|---|---|
| NAME | Dima Kagan |
| GIVEN NAMES | Dima |
| FAMILY NAME | Kagan |
| SIGNATURE | KAGAN D |
| AFFILIATIONS | Ben-Gurion University of the Negev |
| ORCID | 0000-0002-8216-8776 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Ethnic representation analysis of commercial movie posters
In the last decades, global awareness toward the importance of diverse representation has been increasing. The lack of diversity and discrimination toward minorities did not skip the film industry. Here, we examine ethnic bias in the film industry through commercial posters, the industry’s primary advertisement medium for decades. Movie posters are designed to establish the viewer’s initial impression. We developed a novel approach for evaluating…
Zooming Into Video Conferencing Privacy
The unprecedented growth in video conferencing usage is accompanied by multiple security and privacy threats. Importantly, protecting users’ privacy is not always in their own hands. Posting meeting images affects all participants, leading to an easy collection of personal data including age, gender and linkage with participation in other meetings. Here, we explored privacy issues that may be at risk by attending virtual meetings. We extracted pr…
Using data science to understand the film industry’s gender gap
Data science can offer answers to a wide range of social science questions. Here we turn attention to the portrayal of women in movies, an industry that has a significant influence on society, impacting such aspects of life as self-esteem and career choice. To this end, we fused data from the online movie database IMDb with a dataset of movie dialogue subtitles to create the largest available corpus of movie social networks (15,540 networks). Ana…
Generic anomalous vertices detection utilizing a link prediction algorithm
Friend or foe? Fake profile identification in online social networks
Friend or foe? Fake profile identification in online social networks
Generic anomalous vertices detection utilizing a link prediction algorithm
Using data science to understand the film industry’s gender gap
Data science can offer answers to a wide range of social science questions. Here we turn attention to the portrayal of women in movies, an industry that has a significant influence on society, impacting such aspects of life as self-esteem and career choice. To this end, we fused data from the online movie database IMDb with a dataset of movie dialogue subtitles to create the largest available corpus of movie social networks (15,540 networks). Ana…
Ethnic representation analysis of commercial movie posters
In the last decades, global awareness toward the importance of diverse representation has been increasing. The lack of diversity and discrimination toward minorities did not skip the film industry. Here, we examine ethnic bias in the film industry through commercial posters, the industry’s primary advertisement medium for decades. Movie posters are designed to establish the viewer’s initial impression. We developed a novel approach for evaluating…
Zooming Into Video Conferencing Privacy
The unprecedented growth in video conferencing usage is accompanied by multiple security and privacy threats. Importantly, protecting users’ privacy is not always in their own hands. Posting meeting images affects all participants, leading to an easy collection of personal data including age, gender and linkage with participation in other meetings. Here, we explored privacy issues that may be at risk by attending virtual meetings. We extracted pr…
Computer Science (3 works) · Social media (3 works) · Spam and Phishing Detection (3 works) · Artificial Intelligence (2 works) · Internet privacy (2 works) · Media, Gender, and Advertising (2 works) · Sociology (2 works) · World Wide Web (2 works) · Advanced Graph Neural Networks (1 work) · Algorithm (1 work)