Political parties in the United States, and the rest of the world, know fake news to be a threat to democratic process. News media often partakes in the conversation about disinformation and voter suppression. All parties consider the culprit to be the opposing party or foreign actors (state or independent).
Election management bodies consider disinformation a serious threat, but usually lack precise tools to address it. We know that disinformation exists and is affecting modern democracy, but can we trace the sources of disinformation? The simple answer is “Yes, but”.
Using Social Media AI Analytics we can trace disinformation sources – given a clear definition and a mandate
The challenge of addressing disinformation isn’t the technology, but establishing a clear definition and a mandate. Put simply,
- What is fake news, disinformation, or misinformation?
- What can we do about it?
I have discussed this terminology and the challenges of tracing disinformation in an e-book, Using Social Media Data to Transform Election Monitoring.
In 2019, we spent some time analyzing social media accounts that spread untrustworthy or unethical information. By untrustworthy, we mean unreliable or false. By unethical, we mean racist or hateful content that targets a group of people. We referred to such accounts as polluters, simply because there isn’t a Canadian or an American legal term for the culprits. We observed that polluters share three properties, they:
- Have similar or identical arguments
- Create a tight web of connection to other polluters
- Target the ‘Five Eye Countries’: Australia, Canada, New Zealand, United Kingdom, and the United States
The list below presents the top 40 polluters on Twitter in the last few months of 2019. Luckily, the public continues to report these accounts to @twitter and many of them are disabled or deleted by now.
About the Author
Dr. Wael Hassan is the CEO of KI Design. He has publications on privacy, de-identification, and social media analytics for election monitoring. Follow him at @drwhassan. Visit our blog at waelhassan.com or get a copy of Using Social Media Data to Transform Election Monitoring from Amazon.
Top 40 Polluters on Twitter
1) @SteveRedgrave4 2) @oldstocknews 3) @Evenings_Star 4) @Tjooitink 5) @vivianmtl 6) @SteveRedgrave4 7) @calgarykiaguy 8) @heathrodgirs 9) @MousseauJim 10) @SergeHalytsky 11) @SusanIverach 12) @chattycathy1226 13) @RoboHoward 14) @Maureenhommagm1 15) @MikeMw86 16) @KAreYouSerious 17) @lafleurmtl 18) @realmarekfe 19) @wavetossed 20) @Dekenfrank1 21) @jspoupart 22) @NtoAlaska 23) @peterdiane01 24) @1loriking 25) @Ez4u2say_Janis 26) @FouadBoussetta 27) @Real_Dr_Roy 28) @schwarzengel88 29) @bgallagb 30) @hydroqueen 31) @Kimdeerhunter 32) @mmaureen7 33) @OFASDRACING 34) @stephandprissy 35) @AlbertGoldie 36) @CONDESCENDANT 37) @HopeAldridge 38) @MurfAD 39) @TheSeaFarmer