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.
Group formation in large social networks
20061.2k citationsLars Bäckström, D.P. Huttenlocher et al.profile →
Meme-tracking and the dynamics of the news cycle
2009943 citationsJure Leskovec, Lars Bäckström et al.profile →
Countries citing papers authored by Lars Bäckström
Since
Specialization
Citations
This map shows the geographic impact of Lars Bäckström'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 Lars Bäckström with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars Bäckström more than expected).
This network shows the impact of papers produced by Lars Bäckström. 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 Lars Bäckström. The network helps show where Lars Bäckström may publish in the future.
Co-authorship network of co-authors of Lars Bäckström
This figure shows the co-authorship network connecting the top 25 collaborators of Lars Bäckström.
A scholar is included among the top collaborators of Lars Bäckström 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 Lars Bäckström. Lars Bäckström is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Ugander, Johan, Brian Karrer, Lars Bäckström, & Jon Kleinberg. (2013). Graph cluster randomization. 329–337.80 indexed citations
Bäckström, Lars. (2012). Rätten till mineral : en studie om befogenheter och legala inskränkningar i äganderätten till fastighetens beståndsdelar. KTH Publication Database DiVA (KTH Royal Institute of Technology).4 indexed citations
4.
Ugander, Johan, Lars Bäckström, Cameron Marlow, & Jon Kleinberg. (2012). Structural diversity in social contagion. Proceedings of the National Academy of Sciences. 109(16). 5962–5966.412 indexed citations breakdown →
5.
Bäckström, Lars, et al.. (2011). Social media. 327–328.9 indexed citations
6.
Bäckström, Lars & Jure Leskovec. (2011). Supervised random walks. 635–644.653 indexed citations breakdown →
7.
Chang, Jonathan, Itamar Rosenn, Lars Bäckström, & Cameron Marlow. (2010). ePluribus: Ethnicity on Social Networks. Proceedings of the International AAAI Conference on Web and Social Media. 4(1). 18–25.70 indexed citations
8.
Crandall, David, Lars Bäckström, Dan Cosley, et al.. (2010). Inferring social ties from geographic coincidences. Proceedings of the National Academy of Sciences. 107(52). 22436–22441.319 indexed citations
9.
Leskovec, Jure, Lars Bäckström, & Jon Kleinberg. (2009). Meme-tracking and the dynamics of the news cycle. 497–506.943 indexed citations breakdown →
10.
Crandall, David, Lars Bäckström, Daniel P. Huttenlocher, & Jon Kleinberg. (2009). Mapping the world's photos. 761–770.552 indexed citations breakdown →
Bäckström, Lars, Ravi Kumar, Cameron Marlow, Jasmine Novak, & Andrew Tomkins. (2008). Preferential behavior in online groups. 117–117.51 indexed citations
14.
Bäckström, Lars, D.P. Huttenlocher, Jon Kleinberg, & Xiangyang Lan. (2006). Group formation in large social networks. 44–54.1153 indexed citations breakdown →
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.