Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The spreading of misinformation online
20161.3k citationsMichela Del Vicario, Alessandro Bessi et al.Proceedings of the National Academy of Sciencesprofile →
Social bots distort the 2016 U.S. Presidential election online discussion
Countries citing papers authored by Alessandro Bessi
Since
Specialization
Citations
This map shows the geographic impact of Alessandro Bessi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alessandro Bessi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alessandro Bessi more than expected).
Fields of papers citing papers by Alessandro Bessi
This network shows the impact of papers produced by Alessandro Bessi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alessandro Bessi. The network helps show where Alessandro Bessi may publish in the future.
Co-authorship network of co-authors of Alessandro Bessi
This figure shows the co-authorship network connecting the top 25 collaborators of Alessandro Bessi.
A scholar is included among the top collaborators of Alessandro Bessi based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Alessandro Bessi. Alessandro Bessi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zollo, Fabiana, Alessandro Bessi, Michela Del Vicario, et al.. (2017). Debunking in a world of tribes. PLoS ONE. 12(7). e0181821–e0181821.174 indexed citations
Schmidt, Ana Lucía, Fabiana Zollo, Michela Del Vicario, et al.. (2017). Anatomy of news consumption on Facebook. Proceedings of the National Academy of Sciences. 114(12). 3035–3039.178 indexed citations
8.
Vicario, Michela Del, Gianna Vivaldo, Alessandro Bessi, et al.. (2016). Echo Chambers: Emotional Contagion and Group Polarization on Facebook. IRIS Research product catalog (Sapienza University of Rome).324 indexed citations breakdown →
9.
Bessi, Alessandro & Emilio Ferrara. (2016). Social Bots Distort the 2016 US Presidential Election Online Discussion. SSRN Electronic Journal.49 indexed citations
10.
Vicario, Michela Del, Alessandro Bessi, Fabiana Zollo, et al.. (2016). The spreading of misinformation online. Proceedings of the National Academy of Sciences. 113(3). 554–559.1294 indexed citations breakdown →
11.
Bessi, Alessandro, Fabiana Zollo, Michela Del Vicario, et al.. (2016). Users Polarization on Facebook and Youtube. PLoS ONE. 11(8). e0159641–e0159641.153 indexed citations
Bessi, Alessandro, et al.. (2015). Science vs Conspiracy: Collective Narratives in the Age of Misinformation. PLoS ONE. 10(2). e0118093–e0118093.372 indexed citations breakdown →
Bessi, Alessandro, Fabio Petroni, Michela Del Vicario, et al.. (2015). Viral Misinformation. IRIS Research product catalog (Sapienza University of Rome). 355–356.60 indexed citations
Bessi, Alessandro, et al.. (2014). Misinformation in the loop: the emergence ofnarratives in Online Social Networks.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.