Francesca Spezzano's Publications
Francesca Spezzano's Publications
Koren A., Underwood C., Serra E., Spezzano F., Evaluating the Robustness of Fake News Detectors to Adversarial Attacks with Real User Comments. International Journal of Data Science and Analytics (accepted), 2025.
Sakib M.N., Spezzano F., Hamby A., Opposites Attract? Ambivalence in Distinguishing Real and Fake News and Predicting their Spread. In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM 2025) - Posters, Demos, and Datasets track, pp. --, Copenhagen, Denmark, June 23-26, 2025.
Pathak R., Spezzano F., Circumventing Misinformation Controls: Assessing the Robustness of Intervention Strategies in Recommender Systems. In Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2025) - Short paper track, pp. --, New York, USA, June 16--19, 2025.
Spezzano F., Bose D., Integrating Service-Learning Into Social Media Mining Class. In 30th annual ACM conference on Innovation and Technology in Computer Science Education (ITiCSE), pp. -, Nijmegen, The Netherlands, June 30 -- July 2, 2025.
Shrestha A., Duran J., Spezzano F., Serra E., Joint Credibility Estimation of News, User, and Publisher via Role-Relational Graph Convolutional Networks. ACM Transactions on the Web, 18(1):1–24, 2024. Presented at The Web Conference 2025.
Joy A., Shrestha A., Pathak R., Spezzano F., Winiecki D., Modeling the Diffusion of Fake and Real News through the Lens of the Diffusion of Innovations Theory. ACM Transactions on Social Computing, 7(1-4):1-24, 2024. Presented at the Journal Track of the ACM CHI Conference on Human Factors in Computing Systems 2025.
Hamby A., Kim H., Spezzano F., Sensational Stories: The Role of Narrative Characteristics in Distinguishing Real and Fake News and Predicting their Spread. Journal of Business Research, 170:114289 (2024).
Doe C., Knezevic V., Zeng M., Spezzano F., Babinkostova L., Modeling the Time to Share Fake and Real News in Online Social Networks. International Journal of Data Science and Analytics, 18(4): 369-378 (2024).
Raut R., Spezzano F., Enhancing Hate Speech Detection with User Characteristics. International Journal of Data Science and Analytics, 18(4): 445-455 (2024).
Pathak R., Spezzano F., An Empirical Analysis of Intervention Strategies’ Effectiveness for Countering Misinformation Amplification by Recommendation Algorithms. Proceedings of the 46th European Conference on Information Retrieval (ECIR 2024), pp. 285-301, Glasgow, Scotland: March 24-28, 2024.
Pathak R., Spezzano F., Analyzing the Interplay between Diversity of News Recommendations and Misinformation Spread in Social Media. In Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2024) - Late-breaking Results Track, pp. --, Cagliary, Italy: July 1-4, 2024.
Pathak R., Spezzano F., Pera M.S., Understanding the Contribution of Recommendation Algorithms on Misinformation Recommendation and Misinformation Dissemination in Social Networks. ACM Transactions on the Web 17(4):1-26, 2023. Women in RecSys Journal Paper of the Year Awards (senior category) @ RecSys 2024. Presented at CIKM 2024 and RecSys 2024.
Lakha B., Duran J., Serra E., Spezzano F., Prediction of Future Nation-initiated Cyber Attacks from News-based Political Event Graph. In Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2023), special session on Graph Data Science and Applications (GraDSI), pp. --, Thessaloniki, Greece, October 9-13, 2023.
Winiecki D., Spezzano F., Underwood C., Understanding Teenagers Real and Fake News Sharing on Social Media. In Proceedings of the 22nd ACM Interaction Design and Children (IDC 2023) Conference (Work-in-Progress track), pp.598–602, Chicago, USA, June 19-23, 2023.
Pathak R.[*], Lakha B., Raut R.[*], Kim H.[*], Spezzano F., Unveiling Truth Amidst the Pandemic: Multimodal Detection of COVID--19 Unreliable News. In Proceedings of the 5th Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM), pp. 119--131, Amsterdam, The Netherlands, November 21-22, 2023.
Duran J., Sakib M.N., Eisty N., Spezzano F., Evaluating Code Metrics in GitHub Repositories Related to Fake News and Misinformation. In Proceedings of the 21st IEEE/ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2023), pp. --, Orlando, USA, May 23-25, 2023.
Shrestha A., Spezzano F., Characterizing and Predicting Fake News Spreaders in Social Networks. International Journal of Data Science and Analytics, 13(4): 385-398 (2022).
Sakib M.N. and Spezzano F., Automated Detection of Sockpuppet Accounts in Wikipedia. In Proceedings of the 2022 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2022), pp. 155-158, Istanbul, Turkey, Hybrid, Nov 10-13, 2022.
Zhang A., Brookhouse A., Hammer D., Spezzano F., Babinkostova L., Predicting the Influence of Fake and Real News Spreaders (Student Abstract). In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence - Student Abstract and Poster Program, 2022.
Kitzhaber J., Trapp A., Beck J., Serra E., Spezzano F., Hayden E., Roberts J., Predicting RNA Mutation Effects through Machine Learning of High-throughput Ribozyme Experiments (Student Abstract). In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence - Student Abstract and Poster Program, 2022.
Beck J., Roberts J., Kitzhaber J., Trapp A. , Serra E., Spezzano F., Hayden E., Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data. Accepted for publication in Frontiers in Molecular Biosciences, section Biological Modeling and Simulation, 2022.
Spezzano F., Shrestha A., Fails J.A., Stone B., That’s Fake News! Investigating How Readers Identify the Reliability of News When Provided Title, Image, Source Bias, and Full Articles. Proceedings of the ACM on Human Computer Interaction journal (2021). Presented ar the 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2021).
Chamberlain J.M., Spezzano F., Kettler J., Dit B., A Network Analysis of Twitter Interactions by Members of the U.S. Congress. ACM Transactions on Social Computing. Volume 4, Issue 1, pp. 1-22, 2021. Presented at the Journal Track of the ACM CHI Conference on Human Factors in Computing Systems 2021. [Video] [Dataset]
Shrestha A., Spezzano F., Textual Characteristics of News Title and Body to Detect Fake News: A Reproducibility Study. In Proceedings of the 43rd European Conference on Information Retrieval (ECIR), pp. 120 133-, Online, Mar. 28 - Apr. 1, 2021. Best Reproducibility Paper Award. [Code]
Joy A., Shrestha A., Spezzano F., Are You Influenced? Modeling the Diffusion of Fake News in Social Media, In Proceedings of the 2021 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2021), pp. –, Virtual, Nov. 8-11, 2021.
Shrestha A., Spezzano F., An Analysis of People’s Reasoning for Sharing Real and Fake News. Workshop on Misinformation Integrity in Social Networks (MISINFO), Online, Apr. 15, 2021, co-located with The Web Conference, 2021.
Shrestha A., Spezzano F., Pera M.S., An Empirical Analysis of Colloborative Recommender Systems Robustness to Shilling Attacks. OHARS'21: Second Workshop of Online Misinformation- and Harm-Aware Recommender Systems, Online, co-located with the 15th ACM Conference on Recommender Systems (RecSys21), 2021.
Spezzano F., Using Service-Learning in Graduate Curriculum to Address Teenagers Vulnerability to Web Misinformation. In Proceedings of the 26th annual conference on Innovation and Technology in Computer Science Education (ITiCSE), pp. 637–638, Online, Jun. 26 - Jul. 1, 2021.
Shrestha A., Serra E., Spezzano F., Multi-modal Social and Psycho-linguistic Embedding via Recurrent Neural Networks to Identify Depressed Users in On-line Forums. Network Modeling Analysis in Health Informatics and Bioinformatics. 9(1): 22 (2020).
Joshi N., Spezzano F., Green M., Hill E., Detecting Undisclosed Paid Editing in Wikipedia. In Proceedings of The Web Conference 2020, pp. 2899–2905, Taipei, Taiwan, Apr. 20-24, 2020.
Serra E., Shrestha A., Spezzano F., Squicciarini A., DeepTrust: An Automatic Framework to Detect Trustworthy Users in Opinion-based Systems. In Proceedings of the 10th ACM Conference on Data and Application Security and Privacy (CODASPY), pp. 29–38, New Orleans, LA, USA, Mar 16-18, 2020.
Shrestha A., Spezzano F., Gurunathan I., Multi-modal Analysis of Misleading Political News. In Proceedings of the 2nd Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM), pp. 261–276, Leiden, the Netherlands, 2020.
Spezzano F., Gurunathan I., Protecting the Web from Misinformation. Open Source Intelligence and Cyber Crime - Lecture Notes in Social Networks, pp. 1-27, 2020.
Shrestha A., Spezzano F., Joy A., Detecting Fake News Spreaders in Social Networks via Linguistic and Personality Features. Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum, Online, September 22-25, 2020.
Spezzano F., Winiecki D., How Do People Decide Political News Credibility? In Proceedings of the 2020 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2020) – Multidisciplinary track, pp. 602–605, Virtual, Dec 7-10, 2020.
Winiecki D., Kappelman K., Hay B., Joaristi M., Serra E., Spezzano F., Validating Bad Entity Ranking in the Panama Papers via Open-source Intelligence In Proceedings of the 2020 International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI) in conjunction with ASONAM 2020, pp. 752–759, Virtual, Dec 7-10, 2020.
Joaristi M., Serra E., Spezzano F., Detecting Suspicious Entities in Offshore Leaks Networks. Social Network Analysis and Mining. 9(1): 10:1-10:16 (2019).
Gundala L. A., Spezzano F., Estimating Node Indirect Interaction Duration to Enhance Link Prediction. Social Network Analysis and Mining 9(1): 17:1-17:13 (2019).
Spezzano F., Suyehira K., Gundala L. A., Detecting Pages to Protect in Wikipedia across Multiple Languages. Social Network Analysis and Mining 9(1): 10:1-10:16 (2019).
Kansal A., Spezzano F., SQUID: A Scalable System for Querying, Updating and Indexing Dynamic Graph Databases. In Proceedings of the 31st International Conference on Scientific and Statistical Database Management (SSDBM), pp. 218–221, Santa Cruz, CA, USA, Jul 23-25, 2019.
Shrestha A., Spezzano F., Detecting Depressed Users in Online Forums. In Proceedings of the 2019 International Symposium on Network Enabled Health Informatics, Biomedicine, and Bioinformatics (HI-BI-BI) in conjunction with ASONAM 2019, pp. 945–951, Vancouver, Canada, Aug 27-30, 2019.
Shrestha A., Spezzano F., Online Misinformation: From the Deceiver to the Victim. In Proceedings of the 2019 International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI) in conjunction with ASONAM 2019, pp. 847–850, Vancouver, Canada, Aug 27-30, 2019.
Arelli H., Spezzano F., Shrestha A., Editing Behavior Analysis for Predicting Active and Inactive Users in Wikipedia. Influence and Behavior Analysis in Social Networks and Social Media 2019: 127-147, Springer, 2019.
Joaristi M., Serra E., Spezzano F., Inferring Bad Entities through the Panama Papers Network In Proceedings of the 2018 International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI) in conjunction with ASONAM 2018, pp. 767–773, Barcelona, Spain, Aug 28-31, 2018. Best Paper Award.
Gundala L. A., Spezzano F., A Framework for Predicting Links between Indirectly Interacting Nodes. In Proceedings of the 2018 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018), pp. 544–551, Barcelona, Spain, Aug 28-31, 2018. Acceptance rate 15% (full papers).
Shrestha A., Spezzano F., Pera M. S. Who is Really Affected by Fraudulent Reviews? An analysis of shilling attacks on recommender systems in real-world scenarios. In Proceedings of Late-Breaking Results track part of the Twelfth ACM Conference on Recommender Systems (RecSys’18), Vancouver, Canada, Oct 2-7, 2018.
Kansal A., Spezzano F., A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM 2017), pp. 207–216, Singapore, November 6-10, 2017.
Dhakal N., Spezzano F., Xu D., Predicting Friendship Strength for Privacy Preserving: A Case Study on Facebook. In Proceedings of the 2017 International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI) in conjunction with ASONAM 2017, pp. 1096–1103, Sydney, Australia, Aug 1-2, 2017.
Arelli H., Spezzano F., Who Will Stop Contributing? Predicting Inactive Editors in Wikipedia. In Proceedings of the 2017 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2017), pp. 355–358, Sydney, Australia, Jul 31 - Aug 3, 2017.
Green T., Spezzano F., Spammer Users Identification in Wikipedia via Editing Behavior. In Proceedings of the 11th International AAAI Conference on Web and Social Media (ICWSM), pp. 532–535, Montreal, CA, May 15-18, 2017.
Spezzano F., Ensuring the Integrity of Wikipedia: A Data Science Approach. In Proceedings of the 25th Italian Symposium on Advanced Database Systems (SEBD 2017), pp. 98–105, Squillace Lido, Italy, June 25-29, 2017.
Kang C., Kraus S., Molinaro C., Spezzano F., Subrahmanian V., Diffusion Centrality: A Paradigm to Maximize Spread in Social Networks. Artificial Intelligence Journal (AIJ) 239: 70-96 (2016).
Kumar S., Spezzano F., Subrahmanian V., Faloutsos C., Edge Weight Prediction in Weighted Signed Networks. In Proceedings of IEEE International Conference on Data Mining (ICDM), pp. 221-230 , Barcelona, Spain, December 13-15, 2016. Acceptance rate 8.5% (regular papers). Selected as one of the best papers of ICDM’16. Invited for possible publication in Knowledge and Information Systems (KAIS) journal.
Suyehira K., Spezzano F., DePP: A System for Detecting Pages to Protect in Wikipedia. In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), pp. 2081-2084, Indianapolis, USA, October 24-28, 2016.
Joaristi M., Serra E., Spezzano F., Evaluating the Impact of Social Media in Detecting Health-Violating Restaurants. In Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016), pp. 626-633, San Francisco, USA, August 18-21, 2016.
Serra E., Spezzano F., Subrahmanian V., ChoiceGAPs: Competitive Diffusion as a Massive Multi-Player Game in Social Networks. In Proceedings of the 10th International Conference on Scalable Uncertainty Management (SUM 2016), pp. 303-319, Nice, France, September 21 -23, 2016.
Kumar S., Serra E., Spezzano F., Subrahmanian V., Metric Logic Program Explanations for Complex Separator Functions. In Proceedings of the 10th International Conference on Scalable Uncertainty Management (SUM 2016), pp. 199-213, Nice, France, September 21 -23, 2016.
Greco S., Spezzano F., Trubitsyna I., Calautti M., Checking Termination of Bottom-Up Evaluation of Logic Programs with Function Symbols. Theory and Practice of Logic Programming (TPLP) 15(6): 854-889 (2015).
Greco S., Spezzano F., Trubitsyna I., Checking Chase Termination: Cyclicity Analysis and Rewriting Techniques. IEEE Transaction of Knowledge and Data Engineering (TKDE) 27(3): 621-635 (2015).
Serra E., Spezzano F., An Effective GPU-based Approach to Probabilistic Query Confidence Computation. IEEE Transaction of Knowledge and Data Engineering (TKDE) 27(1): 17-31 (2015).
Kumar S., Spezzano F., Subrahmanian V., VEWS: A Wikipedia Vandal Early Warning System. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2015). pp. 607-616 , Sydney, Australia, August 10-13, 2015.
Andrews I., Kumar S., Spezzano F., Subrahmanian V., SPINN: Suspicion Prediction in Nuclear Networks. In Proceedings of the IEEE International Conference on Intelligence and Security Informatics (IEEE ISI 2015), pp. 19–24 , Baltimore, MD, USA, May 26-29, 2015.
Spezzano F., Subrahmanian V., Mannes A. Reshaping Terrorist Networks. Communications of the ACM 57(8): 60-69 (2014).
Kumar S., Spezzano F., Subrahmanian V. Accurately Detecting Trolls in Slashdot Zoo via Decluttering. In Proceedings of the 2014 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), pp. 188–195, Beijing, China, August 17-20, 2014.
Skillicorn D., Spezzano F., Subrahmanian V., Garber M. Understanding South Asian Violent Extremist Group-Group Interactions. In Proceedings of the 2014 International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI) in conjunction with ASONAM 2014, pp. 687–694, Beijing, China, August 18-19, 2014.
Kolaitis P. G., Spezzano F., The Semantics of Aggregate Queries in Data Exchange Revisited. In Proceedings of the 7th International Conference on Scalable Uncertainty Management (SUM 2013), pp. 233–246, Washington DC Area, USA, September 16 -18, 2013.
Spezzano F., Subrahmanian V., Mannes A. STONE: Shaping Terrorist Organizational Network Efficiency. In Proceedings of the 2013 IEEE-ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013), pp. 348–355, Niagara Falls, Canada, August 25 -28, 2013.
Greco S., Molinaro C., Spezzano F., Incomplete Data and Data Dependencies in Relational Databases. Synthesis Lectures on Data Management - Morgan & Claypool Publishers (2012).
Greco S., Spezzano F., Trubitsyna I., On the Termination of Logic Programs with Function Symbols. In Technical Communications of the 28th International Conference on Logic Programming (ICLP 2012), pp. 323–333, Budapest, Hungary, September 4-8, 2012.
Greco S., Spezzano F., Trubitsyna I., Stratification-based Criteria for Checking Chase Termination. In Proceedings of the 20th Italian Symposium on Advanced Database Systems (SEBD 2012), pp. 185–192, Venezia, Italy, June 24-27, 2012.
Greco S., Spezzano F., Trubitsyna I., Stratification Criteria and Rewriting Techniques for Checking Chase Termination. Proceedings of the VLDB Endowment (PVLDB) 4(11): 1158-1168 (2011).
De Francesco A., Greco S., Spezzano F., Trubitsyna I., ChaseT: A Tool for Checking Chase Termination. In Proceedings of the 5th International Conference on Scalable Uncertainty Management (SUM 2011). pp. 520–524, Dayton (Ohio), USA, October 10-12, 2011.
De Francesco A., Spezzano F., Trubitsyna I., ChaseT: A Tool for Checking Chase Termination. In Proceedings of the 19th Italian Symposium on Advanced Database Systems (SEBD 2011), pp. 163–174, Maratea, Italy, June 26-29, 2011.
Greco S., Spezzano F., Chase Termination: A Constraints Rewriting Approach. Proceedings of the VLDB Endowment (PVLDB) 3(1): 93-104 (2010).
Greco S., Molinaro C., Spezzano F., Trubitsyna I., Querying and Updating Inconsistent Databases (Extended Abstract). In Proceedings of the 18th Italian Symposium on Advanced Database Systems (SEBD 2010), pp. 438–445, Rimini, Italy, June 20-23, 2010.
Molinaro C., Spezzano F., Greco S., A System Prototype for Computing Probabilistic Query Answers over Inconsistent Databases. In Proceedings of the 17th Italian Symposium on Advanced Database Systems (SEBD 2009), pp. 9–20, Camogli(GE), Italy, June 21-24, 2009.