Publications
2026
Under review, EPJ Data science
Israel-Hamas War on X: A Case Study of Coordinated Campaigns and Information Integrity

Tuğrulcan Elmas, Filipi Nascimento Silva, Manita Pote, Priyanka Dey, Keng-Chi Chang, Jinyi Ye, Luca Luceri, Cody Buntain, Emilio Ferrara, Alessandro Flammini, Fil Menczer

Analyzes 4.5 million tweets during the 2023 Israel-Hamas War to uncover how coordinated social media campaigns shape crisis information environments. Identifies 11 coordinated groups using multimodal methods — finding that manipulation is fragmented, misleading claims concentrate in just three groups, and no single behavioral signal reliably predicts others. Results inform more targeted content moderation strategies.

2025
ICWSM 2025
Labeled Datasets for Research on Information Operations

Ozgur Can Seckin*, Manita Pote*, Alexander C. Nwala, Lake Yin, Luca Luceri, Alessandro Flammini, Filippo Menczer

* Equal contribution

Presents labeled datasets covering 26 information operation campaigns, combining platform-verified IO posts with over 13M posts by 303k control accounts. Enables researchers to study narratives, network interactions, and engagement strategies of coordinated accounts — and to develop and benchmark IO detection algorithms.

2025
ICWSM 2025
Coordinated Reply Attacks in Influence Operations: Characterization and Detection

Manita Pote, Tuğrulcan Elmas, Alessandro Flammini, Filippo Menczer

Characterizes coordinated reply attacks in influence operations on Twitter, revealing that primary targets are journalists, news media, and politicians. Proposes two supervised ML classifiers — one to detect targeted tweets (AUC 0.88) and one to identify accounts in coordinated attacks (AUC 0.97) — showing that targeted accounts themselves can serve as sensors for influence operation detection.

2024
arXiv 2024
Survey on Embedding Models for Knowledge Graph and its Applications

Manita Pote

A survey of knowledge graph embedding models, covering translation-based and neural network-based approaches that represent entities and relations in low-dimensional vector spaces. Discusses applications leveraging deep learning and social media data, addressing challenges of data sparsity and computational complexity in graph-based knowledge representations.

2024
arXiv 2024
Computational Propaganda Theory and Bot Detection System: Critical Literature Review

Manita Pote

A critical review of computational propaganda — the use of algorithms, automation, and human curation to distribute misleading information on social media for political manipulation. Covers the evolution from classical propaganda theory to modern tactics including social bots and state-organized troll armies used for astroturfing, and surveys bot detection systems developed to counter these threats.

2023
ICWSM 2023
A Multi-Platform Collection of Social Media Posts about the 2022 U.S. Midterm Elections

Rachith Aiyappa*, Matthew R. DeVerna*, Manita Pote*, Wanying Zhao*, Bao Tran Truong*, David Axelrod, Aria Pessianzadeh, Zoher Kachwala, Munjung Kim, Ozgur Can Seckin, Minsuk Kim, Sunny Gandhi, Amrutha Manikonda, Francesco Pierri, Filippo Menczer, Kai-Cheng Yang

* Equal contribution

Introduces MEIU22, a multi-platform dataset of social media posts about the 2022 U.S. Midterm Elections spanning Twitter, Facebook, Instagram, Reddit, and 4chan. Covers 1,011 candidates from October 1 to December 25, 2022, with keyword-based post linking and open-source pipeline code to support future multi-platform research.

2022
ICWSM 2022
Manipulating Twitter Through Deletions

Christopher Torres-Lugo*, Manita Pote*, Alexander C. Nwala, Filippo Menczer

* Equal contribution

Presents a method to estimate user deletion behavior on social media and investigates online manipulation tactics observed through deletion patterns, revealing coordinated inauthentic activity on Twitter.

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