Interactive Proofs for Social Graphs

Author(s):  
Liran Katzir ◽  
Clara Shikhelman ◽  
Eylon Yogev
2021 ◽  
Vol 118 ◽  
pp. 327-338
Author(s):  
Zhixiao Wang ◽  
Chengcheng Sun ◽  
Jingke Xi ◽  
Xiaocui Li

2021 ◽  
Vol 30 (2) ◽  
Author(s):  
Tom Gur ◽  
Yang P. Liu ◽  
Ron D. Rothblum

AbstractInteractive proofs of proximity allow a sublinear-time verifier to check that a given input is close to the language, using a small amount of communication with a powerful (but untrusted) prover. In this work, we consider two natural minimally interactive variants of such proofs systems, in which the prover only sends a single message, referred to as the proof. The first variant, known as -proofs of Proximity (), is fully non-interactive, meaning that the proof is a function of the input only. The second variant, known as -proofs of Proximity (), allows the proof to additionally depend on the verifier's (entire) random string. The complexity of both s and s is the total number of bits that the verifier observes—namely, the sum of the proof length and query complexity. Our main result is an exponential separation between the power of s and s. Specifically, we exhibit an explicit and natural property $$\Pi$$ Π that admits an with complexity $$O(\log n)$$ O ( log n ) , whereas any for $$\Pi$$ Π has complexity $$\tilde{\Omega}(n^{1/4})$$ Ω ~ ( n 1 / 4 ) , where n denotes the length of the input in bits. Our lower bound also yields an alternate proof, which is more general and arguably much simpler, for a recent result of Fischer et al. (ITCS, 2014). Also, Aaronson (Quantum Information & Computation 2012) has shown a $$\Omega(n^{1/6})$$ Ω ( n 1 / 6 ) lower bound for the same property $$\Pi$$ Π .Lastly, we also consider the notion of oblivious proofs of proximity, in which the verifier's queries are oblivious to the proof. In this setting, we show that s can only be quadratically stronger than s. As an application of this result, we show an exponential separation between the power of public and private coin for oblivious interactive proofs of proximity.


2021 ◽  
Vol 7 (3) ◽  
pp. 172
Author(s):  
Elena Kranzeeva ◽  
Evgeny Golovatsky ◽  
Anna Orlova ◽  
Natalia Nyatina ◽  
Anna Burmakina

Open innovations combine the interaction of the authorities and the population in regions of Russia. Social and political interaction of Russian network users demonstrates new open forms of political participation, mobilization practices (initiative appeals, petitions), the use of expert systems data, and remote access technologies. The increasing number of initiatives and the growth of online communities involved in the discussion and adjustment of the results of innovation activities require the use of a big data format. The demand for open innovation based on the principles of transparency of social and political interactions is being updated during COVID-19. This study aims to assess the effectiveness of open innovations in social and political interactions during COVID-19. The innovative practices of communication between the population and authorities were studied using DataMining tools based on digital platforms: “Russian Public Initiative”, “Change.org” and “GoogleTrends”. Users’ social graphs represent the visualization in terms of thematic and territorial groupings. The results obtained allow for a conclusion about the dependence of the regional innovation activities on the openness of their communications and their location relative to authoritative and other types of resources. The physical location of the region (center–border region–periphery) and dependence on implementation at the federal, regional or municipal levels are circumstances influencing the effectiveness of social and political innovations.


2019 ◽  
pp. STOC16-255-STOC16-340
Author(s):  
Omer Reingold ◽  
Guy N. Rothblum ◽  
Ron D. Rothblum
Keyword(s):  

2014 ◽  
Vol 17 (01) ◽  
pp. 1450001 ◽  
Author(s):  
MICHEL CRAMPES ◽  
MICHEL PLANTIÉ

With the widespread social networks on the Internet, community detection in social graphs has recently become an important research domain. Interest was initially limited to unipartite graph inputs and partitioned community outputs. More recently, bipartite graphs, directed graphs and overlapping communities have all been investigated. Few contributions however have encompassed all three types of graphs simultaneously. In this paper, we present a method that unifies community detection for these three types of graphs while at the same time it merges partitioned and overlapping communities. Moreover, the results are visualized in a way that allows for analysis and semantic interpretation. For validation purposes this method is experimented on some well-known simple benchmarks and then applied to real data: photos and tags in Facebook and Human Brain Tractography data. This last application leads to the possibility of applying community detection methods to other fields such as data analysis with original enhanced performances.


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