Investigating Fake and Reliable News Sources Using Complex Networks Analysis
The rise of disinformation in the last years has shed light on the presence of bad actors that produce and spread misleading content every day. Therefore, looking at the characteristics of these actors has become crucial for gaining better knowledge of the phenomenon of disinformation to fight it. T...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2022.886544/full |
| _version_ | 1811242850150514688 |
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| author | Valeria Mazzeo Andrea Rapisarda Andrea Rapisarda Andrea Rapisarda |
| author_facet | Valeria Mazzeo Andrea Rapisarda Andrea Rapisarda Andrea Rapisarda |
| author_sort | Valeria Mazzeo |
| collection | DOAJ |
| description | The rise of disinformation in the last years has shed light on the presence of bad actors that produce and spread misleading content every day. Therefore, looking at the characteristics of these actors has become crucial for gaining better knowledge of the phenomenon of disinformation to fight it. This study seeks to understand how these actors, meant here as unreliable news websites, differ from reliable ones. With this aim, we investigated some well-known fake and reliable news sources and their relationships, using a network growth model based on the overlap of their audience. Then, we peered into the news sites’ sub-networks and their structure, finding that unreliable news sources’ sub-networks are overall disassortative and have a low–medium clustering coefficient, indicative of a higher fragmentation. The k-core decomposition allowed us to find the coreness value for each node in the network, identifying the most connectedness site communities and revealing the structural organization of the network, where the unreliable websites tend to populate the inner shells. By analyzing WHOIS information, it also emerged that unreliable websites generally have a newer registration date and shorter-term registrations compared to reliable websites. The results on the political leaning of the news sources show extremist news sources of any political leaning are generally mostly responsible for producing and spreading disinformation. |
| first_indexed | 2024-04-12T13:57:10Z |
| format | Article |
| id | doaj.art-9c21af1c5f0c495fb48c17a30ff99e25 |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-12T13:57:10Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-9c21af1c5f0c495fb48c17a30ff99e252022-12-22T03:30:20ZengFrontiers Media S.A.Frontiers in Physics2296-424X2022-06-011010.3389/fphy.2022.886544886544Investigating Fake and Reliable News Sources Using Complex Networks AnalysisValeria Mazzeo0Andrea Rapisarda1Andrea Rapisarda2Andrea Rapisarda3Department of Physics and Astronomy “Ettore Majorana”, University of Catania, Catania, ItalyDepartment of Physics and Astronomy “Ettore Majorana”, University of Catania, Catania, ItalyComplexity Science Hub Vienna (CSH), Vienna, AustriaINFN Sezione di Catania, Catania, ItalyThe rise of disinformation in the last years has shed light on the presence of bad actors that produce and spread misleading content every day. Therefore, looking at the characteristics of these actors has become crucial for gaining better knowledge of the phenomenon of disinformation to fight it. This study seeks to understand how these actors, meant here as unreliable news websites, differ from reliable ones. With this aim, we investigated some well-known fake and reliable news sources and their relationships, using a network growth model based on the overlap of their audience. Then, we peered into the news sites’ sub-networks and their structure, finding that unreliable news sources’ sub-networks are overall disassortative and have a low–medium clustering coefficient, indicative of a higher fragmentation. The k-core decomposition allowed us to find the coreness value for each node in the network, identifying the most connectedness site communities and revealing the structural organization of the network, where the unreliable websites tend to populate the inner shells. By analyzing WHOIS information, it also emerged that unreliable websites generally have a newer registration date and shorter-term registrations compared to reliable websites. The results on the political leaning of the news sources show extremist news sources of any political leaning are generally mostly responsible for producing and spreading disinformation.https://www.frontiersin.org/articles/10.3389/fphy.2022.886544/fullcomplex networksfake newsdisinformationaudience overlapsearch engine optimization |
| spellingShingle | Valeria Mazzeo Andrea Rapisarda Andrea Rapisarda Andrea Rapisarda Investigating Fake and Reliable News Sources Using Complex Networks Analysis Frontiers in Physics complex networks fake news disinformation audience overlap search engine optimization |
| title | Investigating Fake and Reliable News Sources Using Complex Networks Analysis |
| title_full | Investigating Fake and Reliable News Sources Using Complex Networks Analysis |
| title_fullStr | Investigating Fake and Reliable News Sources Using Complex Networks Analysis |
| title_full_unstemmed | Investigating Fake and Reliable News Sources Using Complex Networks Analysis |
| title_short | Investigating Fake and Reliable News Sources Using Complex Networks Analysis |
| title_sort | investigating fake and reliable news sources using complex networks analysis |
| topic | complex networks fake news disinformation audience overlap search engine optimization |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2022.886544/full |
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