{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T20:21:41Z","timestamp":1782937301558,"version":"3.54.5"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T00:00:00Z","timestamp":1652140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["825297"],"award-info":[{"award-number":["825297"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["951911"],"award-info":[{"award-number":["951911"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["SGECPD18CA0024"],"award-info":[{"award-number":["SGECPD18CA0024"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"name":"US Department of State Global Engagement Center","award":["825297"],"award-info":[{"award-number":["825297"]}]},{"name":"US Department of State Global Engagement Center","award":["951911"],"award-info":[{"award-number":["951911"]}]},{"name":"US Department of State Global Engagement Center","award":["SGECPD18CA0024"],"award-info":[{"award-number":["SGECPD18CA0024"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The proliferation of online news, especially during the \u201cinfodemic\u201d that emerged along with the COVID-19 pandemic, has rapidly increased the risk of and, more importantly, the volume of online misinformation. Online Social Networks (OSNs), such as Facebook, Twitter, and YouTube, serve as fertile ground for disseminating misinformation, making the need for tools for analyzing the social web and gaining insights into communities that drive misinformation online vital. We introduce the MeVer NetworkX analysis and visualization tool, which helps users delve into social media conversations, helps users gain insights about how information propagates, and provides intuition about communities formed via interactions. The contributions of our tool lie in easy navigation through a multitude of features that provide helpful insights about the account behaviors and information propagation, provide the support of Twitter, Facebook, and Telegram graphs, and provide the modularity to integrate more platforms. The tool also provides features that highlight suspicious accounts in a graph that a user should investigate further. We collected four Twitter datasets related to COVID-19 disinformation to present the tool\u2019s functionalities and evaluate its effectiveness.<\/jats:p>","DOI":"10.3390\/fi14050147","type":"journal-article","created":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T08:31:55Z","timestamp":1652171515000},"page":"147","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["MeVer NetworkX: Network Analysis and Visualization for Tracing Disinformation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0498-7506","authenticated-orcid":false,"given":"Olga","family":"Papadopoulou\u00a0","sequence":"first","affiliation":[{"name":"Centre for Research and Technology Hellas\u2014CERTH, Information Technologies Institute\u2014ITI, 6th km Harilaou-Thermi, Thermi, 57001 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3168-6124","authenticated-orcid":false,"given":"Themistoklis","family":"Makedas\u00a0","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas\u2014CERTH, Information Technologies Institute\u2014ITI, 6th km Harilaou-Thermi, Thermi, 57001 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4379-6099","authenticated-orcid":false,"given":"Lazaros","family":"Apostolidis\u00a0","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas\u2014CERTH, Information Technologies Institute\u2014ITI, 6th km Harilaou-Thermi, Thermi, 57001 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3789-3581","authenticated-orcid":false,"given":"Francesco","family":"Poldi\u00a0","sequence":"additional","affiliation":[{"name":"EU DisinfoLab, Chauss\u00e9e de Charleroi 79, 1060 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5441-7341","authenticated-orcid":false,"given":"Symeon","family":"Papadopoulos","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas\u2014CERTH, Information Technologies Institute\u2014ITI, 6th km Harilaou-Thermi, Thermi, 57001 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6447-9020","authenticated-orcid":false,"given":"Ioannis","family":"Kompatsiaris\u00a0","sequence":"additional","affiliation":[{"name":"Centre for Research and Technology Hellas\u2014CERTH, Information Technologies Institute\u2014ITI, 6th km Harilaou-Thermi, Thermi, 57001 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,10]]},"reference":[{"key":"ref_1","unstructured":"Posetti, J. (2018). News industry transformation: Digital technology, social platforms and the spread of misinformation and disinformation. Journalism,\u2018Fake News\u2019 and Disinformation: A Handbook for Journalism Education and Training, UNESCO. Available online: https:\/\/bit.ly\/2XLRRlA."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1126\/science.aap9559","article-title":"The spread of true and false news online","volume":"359","author":"Vosoughi","year":"2018","journal-title":"Science"},{"key":"ref_3","unstructured":"Meserole, C. (2018). How Misinformation Spreads on Social Media\u2014And What to Do about It, The Brookings Institution. Available online: https:\/\/www.brookings.edu\/blog\/order-from-chaos\/2018\/05\/09\/how-misinformation-spreads-on-social-media-and-what-to-do-about-it."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e26933","DOI":"10.2196\/26933","article-title":"Bots and Misinformation Spread on Social Media: Implications for COVID-19","volume":"23","author":"Giorgi","year":"2021","journal-title":"J. Med. Internet Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-018-06930-7","article-title":"The spread of low-credibility content by social bots","volume":"9","author":"Shao","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1108\/AJIM-09-2013-0094","article-title":"Programmed method: Developing a toolset for capturing and analyzing tweets","volume":"66","year":"2014","journal-title":"Aslib J. Inf. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Marinova, Z., Spangenberg, J., Teyssou, D., Papadopoulos, S., Sarris, N., Alaphilippe, A., and Bontcheva, K. (2020, January 6\u201310). Weverify: Wider and enhanced verification for you project overview and tools. Proceedings of the 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), London, UK.","DOI":"10.1109\/ICMEW46912.2020.9106056"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Teyssou, D., Leung, J.M., Apostolidis, E., Apostolidis, K., Papadopoulos, S., Zampoglou, M., Papadopoulou, O., and Mezaris, V. (2017, January 27). The InVID plug-in: Web video verification on the browser. Proceedings of the First International Workshop on Multimedia Verification, Mountain View, CA, USA.","DOI":"10.1145\/3132384.3132387"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Peeters, S., and Hagen, S. (2021). The 4CAT capture and analysis toolkit: A modular tool for transparent and traceable social media research. SSRN, 3914892. Available online: https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3914892.","DOI":"10.2139\/ssrn.3914892"},{"key":"ref_10","unstructured":"Wang, B., Zubiaga, A., Liakata, M., and Procter, R. (2015). Making the Most of Tweet-Inherent Features for Social Spam Detection on Twitter. arXiv."},{"key":"ref_11","first-page":"13","article-title":"Fake Account Detection in Twitter Based on Minimum Weighted Feature set","volume":"10","author":"ElAzab","year":"2016","journal-title":"World Acad. Sci. Eng. Technol. Int. J. Comput. Inf. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Mateen, M., Iqbal, M.A., Aleem, M., and Islam, M.A. (2017, January 10\u201314). A hybrid approach for spam detection for Twitter. Proceedings of the 2017 14th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Islamabad, Pakistan.","DOI":"10.1109\/IBCAST.2017.7868095"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1109\/TIFS.2013.2267732","article-title":"Empirical Evaluation and New Design for Fighting Evolving Twitter Spammers","volume":"8","author":"Yang","year":"2013","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"101715","DOI":"10.1016\/j.cose.2020.101715","article-title":"A one-class classification approach for bot detection on Twitter","volume":"91","author":"Monroy","year":"2020","journal-title":"Comput. Secur."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"112003","DOI":"10.1109\/ACCESS.2020.3002940","article-title":"Detection of Social Network Spam Based on Improved Extreme Learning Machine","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Alom, Z., Carminati, B., and Ferrari, E. (2018, January 28\u201331). Detecting Spam Accounts on Twitter. Proceedings of the 2018 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, Spain.","DOI":"10.1109\/ASONAM.2018.8508495"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1080\/10584609.2019.1661888","article-title":"Political Astroturfing on Twitter: How to Coordinate a Disinformation Campaign","volume":"37","author":"Keller","year":"2019","journal-title":"Political Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102317","DOI":"10.1016\/j.ipm.2020.102317","article-title":"SimilCatch: Enhanced social spammers detection on Twitter using Markov Random Fields","volume":"57","author":"Honeine","year":"2020","journal-title":"Inf. Process. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"68140","DOI":"10.1109\/ACCESS.2019.2918196","article-title":"Spammer Detection and Fake User Identification on Social Networks","volume":"7","author":"Masood","year":"2019","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hansen, D., Shneiderman, B., and Smith, M.A. (2010). Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Morgan Kaufmann.","DOI":"10.1016\/B978-0-12-382229-1.00002-3"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"106","DOI":"10.33621\/jdsr.v3i1.64","article-title":"The twitter explorer: A framework for observing Twitter through interactive networks","volume":"3","author":"Pournaki","year":"2021","journal-title":"Digit. Soc. Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Karmakharm, T., Aletras, N., and Bontcheva, K. (2019, January 3\u20137). Journalist-in-the-loop: Continuous learning as a service for rumour analysis. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, Hong Kong, China.","DOI":"10.18653\/v1\/D19-3020"},{"key":"ref_23","unstructured":"Bevensee, E., Aliapoulios, M., Dougherty, Q., Baumgartner, J., Mccoy, D., and Blackburn, J. (2020, January 8\u201311). SMAT: The social media analysis toolkit. Proceedings of the 14th International AAAI Conference on Web and Social Media, Atlanta, GA, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.21105\/joss.01706","article-title":"Botslayer: Real-time detection of bot amplification on twitter","volume":"4","author":"Hui","year":"2019","journal-title":"J. Open Source Softw."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Liu, X., Li, Q., Nourbakhsh, A., Fang, R., Thomas, M., Anderson, K., Kociuba, R., Vedder, M., Pomerville, S., and Wudali, R. (2016, January 24\u201328). Reuters tracer: A large scale system of detecting & verifying real-time news events from twitter. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, Indianapolis, IN, USA.","DOI":"10.1145\/2983323.2983363"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ram, R., Kong, Q., and Rizoiu, M.A. (2021, January 8\u201312). Birdspotter: A Tool for Analyzing and Labeling Twitter Users. Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event.","DOI":"10.1145\/3437963.3441695"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","article-title":"Fast unfolding of communities in large networks","volume":"2008","author":"Blondel","year":"2008","journal-title":"J. Stat. Mech. Theory Exp."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bruls, M., Huizing, K., and Van Wijk, J.J. (2000). Squarified treemaps. Data visualization 2000, Springer.","DOI":"10.1007\/978-3-7091-6783-0_4"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Jacomy, M., Venturini, T., Heymann, S., and Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0098679"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Majeed, S., Uzair, M., Qamar, U., and Farooq, A. (2020, January 5\u20137). Social Network Analysis Visualization Tools: A Comparative Review. Proceedings of the 2020 IEEE 23rd International Multitopic Conference (INMIC), Bahawalpur, Pakistan.","DOI":"10.1109\/INMIC50486.2020.9318162"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1278932","DOI":"10.1155\/2017\/1278932","article-title":"Empirical comparison of visualization tools for larger-scale network analysis","volume":"2017","author":"Pavlopoulos","year":"2017","journal-title":"Adv. Bioinform."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/5\/147\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:08:42Z","timestamp":1760137722000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/5\/147"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,10]]},"references-count":31,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["fi14050147"],"URL":"https:\/\/doi.org\/10.3390\/fi14050147","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,10]]}}}