
doi: 10.22161/ijllc.3.1.3
Misinformation has shifted political narratives across the globe. Because information shared over social media platforms lack traditional publishers and editors, the public is more susceptible to consuming information that is untrue. During the 2016 U.S. presidential election, the Russian government sponsored information operatives to spread misleading and/or false claims through social media. This study defines a method for automated detection of misinformation on social media using machine learning.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
