Link Prediction in Social Networks Using Computationally Efficient Topological Features. - Michael Fire; Lena Tenenboim; Ofrit Lesser; Rami Puzis; Lior Rokach; Yuval Elovici (SocialCom/PASSAT, 2011)

Predicting Student Exam's Scores by Analyzing Social Network Data. - Michael Fire; Gilad Katz; Yuval Elovici; Bracha Shapira; Lior Rokach (AMT, 2012)

How Many Makes a Crowd? On the Evolution of Learning as a Factor of Community Coverage. - Yaniv Altshuler; Michael Fire; Nadav Aharony; Yuval Elovici; Alex Pentland (SBP, 2012)

Incremental Learning with Accuracy Prediction of Social and Individual Properties from Mobile-Phone Data. - Yaniv Altshuler; Nadav Aharony; Michael Fire; Yuval Elovici; Alex Pentland (SocialCom/PASSAT, 2012)

Organizational Intrusion: Organization Mining Using Socialbots. - Aviad Elyashar; Michael Fire; Dima Kagan; Yuval Elovici (SocialInformatics, 2012)

Social Network Based Search for Experts - Yehonatan Bitton; Michael Fire; Dima Kagan; Bracha Shapira; Lior Rokach; Judit Bar-Ilan (CoRR, 2012)

Homing socialbots: intrusion on a specific organization's employee using Socialbots. - Aviad Elyashar; Michael Fire; Dima Kagan; Yuval Elovici (ASONAM, 2013)

Trade-Offs in Social and Behavioral Modeling in Mobile Networks. - Yaniv Altshuler; Michael Fire; Nadav Aharony; Zeev Volkovich; Yuval Elovici; Alex Pentland (SBP, 2013)

Detecting Anomalous Behaviors Using Structural Properties of Social Networks. - Yaniv Altshuler; Michael Fire; Erez Shmueli; Yuval Elovici; Alfred M. Bruckstein; Alex Pentland; David Lazer (SBP, 2013)

Entity Matching in Online Social Networks. - Olga Peled; Michael Fire; Lior Rokach; Yuval Elovici (SocialCom, 2013)

Ethical Considerations when Employing Fake Identities in OSN for Research. - Yuval Elovici; Michael Fire; Amir Herzberg; Haya Schulmann (CoRR, 2013)

Facebook Applications' Installation and Removal: A Temporal Analysis. - Dima Kagan; Michael Fire; Aviad Elyashar; Yuval Elovici (CoRR, 2013)

Organization Mining Using Online Social Networks - Michael Fire; Rami Puzis; Yuval Elovici (CoRR, 2013)

Online Social Networks: Threats and Solutions Survey - Michael Fire; Roy Goldschmidt; Yuval Elovici (CoRR, 2013)

Computationally efficient link prediction in a variety of social networks. - Michael Fire; Lena Tenenboim-Chekina; Rami Puzis; Ofrit Lesser; Lior Rokach; Yuval Elovici (ACM Trans. Intell. Syst. Technol., 2013)

Online Social Networks: Threats and Solutions. - Michael Fire; Roy Goldschmidt; Yuval Elovici (IEEE Commun. Surv. Tutorials, 2014)

Quantitative Analysis of Genealogy Using Digitised Family Trees. - Michael Fire; Thomas Chesney; Yuval Elovici (CoRR, 2014)

Ethical Considerations when Employing Fake Identities in Online Social Networks for Research. - Yuval Elovici; Michael Fire; Amir Herzberg; Haya Schulmann (Sci. Eng. Ethics, 2014)

Friend or foe? Fake profile identification in online social networks. - Michael Fire; Dima Kagan; Aviad Elyashar; Yuval Elovici (Soc. Netw. Anal. Min., 2014)

Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population. - Michael Fire; Yuval Elovici (ACM Trans. Intell. Syst. Technol., 2015)

Guided socialbots: Infiltrating the social networks of specific organizations' employees. - Aviad Elyashar; Michael Fire; Dima Kagan; Yuval Elovici (AI Commun., 2016)

Analyzing Complex Network User Arrival Patterns and Their Effect on Network Topologies. - Michael Fire; Carlos Guestrin (CoRR, 2016)

Unsupervised Anomalous Vertices Detection Utilizing Link Prediction Algorithms. - Dima Kagan; Michael Fire; Yuval Elovici (CoRR, 2016)

Matching entities across online social networks. - Olga Peled; Michael Fire; Lior Rokach; Yuval Elovici (Neurocomputing, 2016)

Exploring Online Ad Images Using a Deep Convolutional Neural Network Approach. - Michael Fire; Jonathan Schler (iThings/GreenCom/CPSCom/SmartData, 2017)

The Rise and Fall of Network Stars. - Michael Fire; Carlos Guestrin (CoRR, 2017)

Over-Optimization of Academic Publishing Metrics: Observing Goodhart's Law in Action. - Michael Fire; Carlos Guestrin (CoRR, 2018)

Generic anomalous vertices detection utilizing a link prediction algorithm. - Dima Kagan; Yuval Elovici; Michael Fire (Soc. Netw. Anal. Min., 2018)

Using Data Science to Understand the Film Industry's Gender Gap. - Dima Kagan; Thomas Chesney; Michael Fire (CoRR, 2019)

It Runs in the Family: Searching for Similar Names using Digitized Family Trees. - Aviad Elyashar; Rami Puzis; Michael Fire (CoRR, 2019)

Imputation of Missing Boarding Stop Information in Smart Card Data with Machine Learning Methods. - Nadav Shalit; Michael Fire; Eran Ben-Elia (IDEAL (1), 2020)

Using Data Mining for Infrastructure and Safety Violations Discovery in Cities. - Doron Laadan; Eyal Arviv; Michael Fire (ISC2, 2020)

Imputing Missing Boarding Stations With Machine Learning Methods. - Nadav Shalit; Michael Fire; Eran Ben-Elia (CoRR, 2020)

How Does That Sound? Multi-Language SpokenName2Vec Algorithm Using Speech Generation and Deep Learning. - Aviad Elyashar; Rami Puzis; Michael Fire (CoRR, 2020)

Zooming Into Video Conferencing Privacy and Security Threats. - Dima Kagan; Galit Fuhrmann Alpert; Michael Fire (CoRR, 2020)

The rise and fall of network stars: Analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time. - Michael Fire; Carlos Guestrin (Inf. Process. Manag., 2020)

Automatic Large Scale Detection of Red Palm Weevil Infestation using Aerial and Street View Images. - Dima Kagan; Galit Fuhrmann Alpert; Michael Fire (CoRR, 2021)

How does that name sound? Name representation learning using accent-specific speech generation. - Aviad Elyashar; Rami Puzis; Michael Fire (Knowl. Based Syst., 2021)

CompanyName2Vec: Company Entity Matching based on Job Ads. - Ran Ziv; Ilan Gronau; Michael Fire (DSAA, 2022)

Trends in computer science research within European countries. - Dima Kagan; Michael Fire; Galit Fuhrmann Alpert (Commun. ACM, 2022)

Ethnic Representation Analysis of Commercial Movie Posters. - Dima Kagan; Mor Levy; Michael Fire; Galit Fuhrmann Alpert (CoRR, 2022)

Malicious Source Code Detection Using Transformer. - Chen Tsfaty; Michael Fire (CoRR, 2022)

Zooming into Abnormal Events in Video Conferencing. - Shmuel Horowitz; Dima Kagan; Galit Fuhrmann Alpert; Michael Fire (IEEE Big Data, 2023)

Large-Scale Shill Bidder Detection in E-commerce. - Michael Fire; Rami Puzis; Dima Kagan; Yuval Elovici (IDEAS, 2023)

Interruptions detection in video conferences. - Shmuel Horowitz; Dima Kagan; Galit Fuhrmann Alpert; Michael Fire (CoRR, 2023)

Short Run Transit Route Planning Decision Support System Using a Deep Learning-Based Weighted Graph. - Nadav Shalit; Michael Fire; Dima Kagan; Eran Ben-Elia (CoRR, 2023)

It Runs in the Family: Unsupervised Algorithm for Alternative Name Suggestion Using Digitized Family Trees. - Aviad Elyashar; Rami Puzis; Michael Fire (IEEE Trans. Knowl. Data Eng., 2023)

A supervised machine learning model for imputing missing boarding stops in smart card data. - Nadav Shalit; Michael Fire; Eran Ben-Elia (Public Transp., 2023)

Malicious source code detection using a translation model. - Chen Tsfaty; Michael Fire (Patterns, 2023)

Co-Membership-based Generic Anomalous Communities Detection. - Shay Lapid; Dima Kagan; Michael Fire (Neural Process. Lett., 2023)

Open framework for analyzing public parliaments data. - Shai Berkovitz; Amit Mazuz; Michael Fire (J. Big Data, 2023)

A Novel Method for News Article Event-Based Embedding. - Koren Ishlach; Itzhak Ben-David; Michael Fire; Lior Rokach (CoRR, 2024)

Shaping History: Advanced Machine Learning Techniques for the Analysis and Dating of Cuneiform Tablets over Three Millennia. - Danielle Kapon; Michael Fire; Shai Gordin (CoRR, 2024)

Zooming Into Video Conferencing Privacy. - Dima Kagan; Galit Fuhrmann Alpert; Michael Fire (IEEE Trans. Comput. Soc. Syst., 2024)

VANPY: Voice Analysis Framework. - Gregory Koushnir; Michael Fire; Galit Fuhrmann Alpert; Dima Kagan (CoRR, 2025)

Behind the Byline: A Large-Scale Study of Scientific Author Contributions. - Itai Assraf; Michael Fire (CoRR, 2025)

Dark LLMs: The Growing Threat of Unaligned AI Models. - Michael Fire; Yitzhak Elbazis; Adi Wasenstein; Lior Rokach (CoRR, 2025)

Framework of Voting Prediction of Parliament Members. - Zahi Mizrahi; Shai Berkovitz; Nimrod Talmon; Michael Fire (CoRR, 2025)

A Comprehensive Machine Learning Framework for Micromobility Demand Prediction. - Omri Porat; Michael Fire; Eran Ben-Elia (CoRR, 2025)

Analyzing key users' behavior trends in volunteer-based networks. - Nofar Piterman; Tamar Makov; Michael Fire (J. Big Data, 2025)