iTracing

iTracing: Automatic Misinformation Fact-Checking

Principal Investigator: Ciprian-Octavian TRUICĂ

Project Partners: Adrian Paschke (Freie Universität Berlin / Fraunhofer FOKUS)

Funding Agency: German Academic Exchange Service (DAAD)

Grant no.: 57693448

Overview

The rapid rise of digital misinformation poses a massive threat to public health, social stability, and democratic processes. While traditional fact-checking relies heavily on manual human verification, this approach is far too slow and labor-intensive to keep pace with the real-time spread of viral claims. iTracing is an automated, real-time fact-checking system designed to identify and mitigate misinformation at scale.

Key Objectives

Veracity Prediction: Analyze the textual content and source credibility of incoming claims using novel Machine Learning (ML) and Deep Learning (DL) architectures.
Network-Based Fact-Checking: Integrate network science to trace how information travels and use these propagation patterns to improve veracity detection.

Innovation and Impact

iTracing moves beyond traditional text analysis by combining cutting-edge AI models with network-based diffusion tracing. By analyzing both what is being said and how it spreads through social networks, the project delivers a highly scalable, real-time solution that significantly advances the state-of-the-art in digital trust and safety.

Publications

Journals

2025

Elena-Simona Apostol, Alin-Georgian Pisică, Ciprian-Octavian Truică. ATESA-BÆRT: A heterogeneous ensemble learning model for Aspect-Based Sentiment Analysis. Knowledge-Based Systems, 326:1-13(113987), ISSN 0950-7051, September 2025. DOI: 10.1016/j.knosys.2025.113987 (Q1 Journal)
Ciprian-Octavian Truică, Elena-Simona Apostol, Marius Marogel, Adrian Paschke. GETAE: Graph Information Enhanced Deep Neural NeTwork Ensemble. Expert Systems with Applications, 275:1-14(126984), ISSN 0957-4174, May 2025, DOI: 10.1016/j.eswa.2025.126984 (Q1 Journal) [pdf]
Alexandru Petrescu, Ciprian-Octavian Truică, Elena-Simona Apostol, Adrian Paschke. EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture. IEEE Transactions on Affective Computing, 16(2): 555-572, ISSN: 1949-3045, April 2025, DOI: 10.1109/TAFFC.2024.3434355 (Q1 Journal) [pdf]

2024

Elena-Simona Apostol, Ciprian-Octavian Truică, Adrian Paschke.ContCommRTD: A Distributed Content-Based Misinformation-Aware Community Detection System for Real-Time Disaster Reporting. IEEE Transactions on Knowledge and Data Engineering, 36(11):5811-5822, ISSN: 1041-4347, November 2024, DOI: 10.1109/TKDE.2024.3417232 (Q1 Journal) [pdf]
Elena-Simona Apostol, Özgur Coban, Ciprian-Octavian Truică. CONTAIN: A community-based algorithm for network immunization. Engineering Science and Technology, an International Journal. 55:1-10(101728), ISSN 2215-0986, July 2024. DOI: 10.1016/j.jestch.2024.101728 (Q1 Journal) [pdf]

Conferences

2024

Ciprian-Octavian Truică, Ana-Teodora Constantinescu, Elena-Simona Apostol. StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms. IEEE International Conference on Intelligent Computer Communication and Processing (ICCP 2024), p.1-5, October 2024 DOI: 10.1109/ICCP63557.2024.10793051 (Rank National: Romania Conference)
Alexandru Petrescu, Ciprian-Octavian Truică, Elena-Simona Apostol. Language-based Mixture of Transformers for EXIST2024. Conference and Labs of the Evaluation Forum (CLEF2024), p. 1157-1164, September 2024 [link] [pdf]
Elena-Simona Apostol, Adrian-Cosmin Cojocaru, Ciprian-Octavian Truică. Large-Scale Graphs Community Detection using Spark GraphFrames, The 23rd International Symposium on Parallel and Distributed Computing (ISPDC 2024), p. 1-5, July 2024. DOI: 10.1109/ISPDC62236.2024.10705389 (Rank C Conference)

Software

ATESA-BÆRT: https://github.com/DS4AI-UPB/ATESA-BAERT
GETAE: https://github.com/DS4AI-UPB/GETAE
CONTAIN: https://github.com/DS4AI-UPB/CONTAIN
StopHC: https://github.com/DS4AI-UPB/StopHC_HarmfulContentMitigation
Spark Dataframes Community Detection: https://github.com/DS4AI-UPB/CommunityDetection-DataframesSpark

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