arXiv subjects

Dmitry Zinoviev

Publications and source records attributed to Dmitry Zinoviev.

At least 19 recordsLinked to original sources

arXiv2024

Discrete Event Simulation: It's Easy with SimPy!

This paper introduces the practicalities and benefits of using SimPy, a discrete event simulation (DES) module written in Python, for modeling and simulating complex systems. Through a step-by-step exploration of the classical Dining Philosophers Problem, we demonstrate how SimPy enables the efficient construction of discrete event models, emphasizing system states, transitions, and event handling. We extend the scenario to introduce resources, such as chopsticks, to model contention and deadlock conditions, and showcase SimPy's capabilities in managing these scenarios. Furthermore, we explore the integration of SimPy with other Python libraries for statistical analysis, showcasing how simulation results inform system design and optimization. The versatility of SimPy is further highlighted through additional modeling scenarios, including resource constraints and customer service interactions, providing insights into the process of building, debugging, simulating, and optimizing models for a wide range of applications. This paper aims to make DES accessible to practitioners and researchers alike, emphasizing the ease with which complex simulations can be constructed, analyzed, and visualized using SimPy and the broader Python ecosystem.

cs.MS↗

arXiv2023

The "Non-Musk Effect" at Twitter

Elon Musk has long been known to significantly impact Wall Street through his controversial statements and actions, particularly through his own use of social media. An innovator and visionary entrepreneur, Musk is often considered a poster boy for all entrepreneurs worldwide. It is, thus, interesting to examine the effect that Musk might have on Main Street, i.e., on the social media activity of other entrepreneurs. In this research, we study and quantify this "Musk Effect," i.e., the impact of Musk's recent and highly publicized acquisition of Twitter on the tweeting activity of entrepreneurs. Using a dataset consisting of 9.94 million actual tweets from 47,190 self-declared entrepreneurs from seven English-speaking countries (US, Australia, New Zealand, UK, Canada, South Africa, and Ireland) spanning 71 weeks and encompassing the entire period from the rumor that Musk may buy Twitter till the completion of the acquisition, we find that only about 2.5% of the entrepreneurs display a significant change in their tweeting behavior over the time. We believe that our study is one of the first works to examine the effect of Musk's acquisition of Twitter on the actual tweeting behavior of Twitter users (entrepreneurs). By quantifying the impact of the Musk Effect on Main Street, we provide a comparison with the effect Musk's actions have on Wall Street. Finally, our systematic identification of the characteristics of entrepreneurs most affected by the Musk Effect has practical implications for academics and practitioners alike.

cs.SI↗

arXiv2021

Sockpuppet Detection: a Telegram case study

In Online Social Networks (OSN) numerous are the cases in which users create multiple accounts that publicly seem to belong to different people but are actually fake identities of the same person. These fictitious characters can be exploited to carry out abusive behaviors such as manipulating opinions, spreading fake news and disturbing other users. In literature this problem is known as the Sockpuppet problem. In our work we focus on Telegram, a wide-spread instant messaging application, often known for its exploitation by members of organized crime and terrorism, and more in general for its high presence of people who have offensive behaviors.

cs.SI↗

arXiv2020

Complex Network Analysis of North American Institutions of Higher Education on Twitter

North American institutions of higher education (IHEs): universities, 4- and 2-year colleges, and trade schools -- are heavily present and followed on Twitter. An IHE Twitter account, on average, has 20,000 subscribers. Many of them follow more than one IHE, making it possible to construct an IHE network, based on the number of co-followers. In this paper, we explore the structure of a network of 1,435 IHEs on Twitter. We discovered significant correlations between the network attributes: various centralities and clustering coefficients -- and IHEs' attributes, such as enrollment, tuition, and religious/racial/gender affiliations. We uncovered the community structure of the network linked to homophily -- such that similar followers follow similar colleges. Additionally, we analyzed the followers' self-descriptions and identified twelve overlapping topics that can be traced to the followers' group identities.

cs.SI↗

arXiv2020

Network Analysis of the 2016 Presidential Campaign Tweets

We applied complex network analysis to ~27,000 tweets posted by the 2016 presidential election's principal participants in the USA. We identified the stages of the election campaigns and the recurring topics addressed by the candidates. Finally, we revealed the leader-follower relationships between the candidates. We conclude that Secretary Hillary Clinton's Twitter performance was subordinate to that of Donald Trump, which may have been one factor that led to her electoral defeat.

cs.SI↗

arXiv2020

A Social Network of Russian "Kompromat"

"Kompromat" (the Russian word for "compromising material") has been efficiently used to harass Russian political and business elites since the days of the USSR. Online crowdsourcing projects such as "RuCompromat" made it possible to catalog and analyze kompromat using quantitative techniques -- namely, social network analysis. In this paper, we constructed a social network of 11,000 Russian and foreign nationals affected by kompromat in Russia in 1991 -- 2020. The network has an excellent modular structure with 62 dense communities. One community contains prominent American officials, politicians, and entrepreneurs (including President Donald Trump) and appears to concern Russia's controversial interference in the 2016 U.S. presidential elections. Various network centrality measures identify seventeen most central kompromat figures, with President Vladimir Putin solidly at the top. We further reveal four types of communities dominated by entrepreneurs, politicians, bankers, and law enforcement officials ("siloviks"), the latter disjointed from the first three.

cs.SI↗

arXiv2017

Networks of Music Groups as Success Predictors

More than 4,600 non-academic music groups emerged in the USSR and post-Soviet independent nations in 1960--2015, performing in 275 genres. Some of the groups became legends and survived for decades, while others vanished and are known now only to select music history scholars. We built a network of the groups based on sharing at least one performer. We discovered that major network measures serve as reasonably accurate predictors of the groups' success. The proposed network-based success exploration and prediction methods are transferable to other areas of arts and humanities that have medium- or long-term team-based collaborations.

cs.SI↗

arXiv2015

Building Mini-Categories in Product Networks

We constructed a product network based on the sales data collected and provided by a Fortune 500 speciality retailer. The structure of the network is dominated by small isolated components, dense clique-based communities, and sparse stars and linear chains and pendants. We used the identified structural elements (tiles) to organize products into mini-categories -- compact collections of potentially complementary and substitute items. The mini-categories extend the traditional hierarchy of retail products (group - class - subcategory) and may serve as building blocks towards exploration of consumer projects and long-term customer behavior.

cs.SI↗

arXiv2014

Mitigation of Delayed Management Costs in Transaction-Oriented Systems

Abundant examples of complex transaction-oriented networks (TONs) can be found in a variety of disciplines, including information and communication technology, finances, commodity trading, and real estate. A transaction in a TON is executed as a sequence of subtransactions associated with the network nodes, and is committed if every subtransaction is committed. A subtransaction incurs a two-fold overhead on the host node: the fixed transient operational cost and the cost of long-term management (e.g. archiving and support) that potentially grows exponentially with the transaction length. If the overall cost exceeds the node capacity, the node fails and all subtransaction incident to the node, and their parent distributed transactions, are aborted. A TON resilience can be measured in terms of either external workloads or intrinsic node fault rates that cause the TON to partially or fully choke. We demonstrate that under certain conditions, these two measures are equivalent. We further show that the exponential growth of the long-term management costs can be mitigated by adjusting the effective operational cost: in other words, that the future maintenance costs could be absorbed into the transient operational costs.

cs.DC↗

arXiv2014

Co-Evolution of Friendship and Publishing in Online Blogging Social Networks

In the past decade, blogging web sites have become more sophisticated and influential than ever. Much of this sophistication and influence follows from their network organization. Blogging social networks (BSNs) allow individual bloggers to form contact lists, subscribe to other blogs, comment on blog posts, declare interests, and participate in collective blogs. Thus, a BSN is a bimodal venue, where users can engage in publishing (post) as well as in social (make friends) activities. In this paper, we study the co-evolution of both activities. We observed a significant positive correlation between blogging and socializing. In addition, we identified a number of user archetypes that correspond to "mainly bloggers," "mainly socializers," etc. We analyzed a BSN at the level of individual posts and changes in contact lists and at the level of trajectories in the friendship-publishing space. Both approaches produced consistent results: the majority of BSN users are passive readers; publishing is the dominant active behavior in a BSN; and social activities complement blogging, rather than compete with it.

cs.SI↗

arXiv2014

Peer Ratings in Massive Online Social Networks

Instant quality feedback in the form of online peer ratings is a prominent feature of modern massive online social networks (MOSNs). It allows network members to indicate their appreciation of a post, comment, photograph, etc. Some MOSNs support both positive and negative (signed) ratings. In this study, we rated 11 thousand MOSN member profiles and collected user responses to the ratings. MOSN users are very sensitive to peer ratings: 33% of the subjects visited the researcher's profile in response to rating, 21% also rated the researcher's profile picture, and 5% left a text comment. The grades left by the subjects are highly polarized: out of the six available grades, the most negative and the most positive are also the most popular. The grades fall into three almost equally sized categories: reciprocal, generous, and stingy. We proposed quantitative measures for generosity, reciprocity, and benevolence, and analyzed them with respect to the subjects' demographics.

cs.SI↗

arXiv2013

Simulating Resilience in Transaction-Oriented Networks

The power of networks manifests itself in a highly non-linear amplification of a number of effects, and their weakness - in propagation of cascading failures. The potential systemic risk effects can be either exacerbated or mitigated, depending on the resilience characteristics of the network. The goals of this paper are to study some characteristics of network amplification and resilience. We simulate random Erdos-Renyi networks and measure amplification by varying node capacity, transaction volume, and expected failure rates. We discover that network throughput scales almost quadratically with respect to the node capacity and that the effects of excessive network load and random and irreparable node faults are equivalent and almost perfectly anticorrelated. This knowledge can be used by capacity planners to determine optimal reliability requirements that maximize the optimal operational regions.

cs.DC↗

arXiv2012

Clown: a Microprocessor Simulator for Operating System Studies

In this paper, I present the design and implementation of Clown--a simulator of a microprocessor-based computer system specifically optimized for teaching operating system courses at undergraduate or graduate levels. The package includes the simulator itself, as well as a collection of basic I/O devices, an assembler, a linker, and a disk formatter. The simulator architecturally resembles mainstream microprocessors from the Intel 80386 family, but is much easier to learn and program. The simulator is fast enough to be used as an emulator--in the direct user interaction mode.

cs.OH↗

arXiv2012

Semantic Networks of Interests in Online NSSI Communities

Persons who engage in non-suicidal self-injury (NSSI), often conceal their practices which limits the examination and understanding of those who engage in NSSI. The goal of this research is to utilize public online social networks (namely, in LiveJournal, a major blogging network) to observe the NSSI population's communication in a naturally occurring setting. Specifically, LiveJournal users can publicly declare their interests. We collected the self-declared interests of 22,000 users who are members of or participate in 43 NSSI-related communities. We extracted a bimodal socio-semantic network of users and interests based on their similarity. The semantic subnetwork of interests contains NSSI terms (such as "self-injury" and "razors"), references to music performers (such as "Nine Inch Nails"), and general daily life and creativity related terms (such as "poetry" and "boys"). Assuming users are genuine in their declarations, the words reveal distinct patterns of interest and may signal keys to NSSI.

cs.SI↗

arXiv2011

Parametric Estimation of the Ultimate Size of Hypercomputers

The performance of the emerging petaflops-scale supercomputers of the nearest future (hypercomputers) will be governed not only by the clock frequency of the processing nodes or by the width of the system bus, but also by such factors as the overall power consumption and the geometric size. In this paper, we study the influence of such parameters on one of the most important characteristics of a general purpose computer - on the degree of multithreading that must be present in an application to make the use of the hypercomputer justifiable. Our major finding is that for the class of applications with purely random memory access patterns "super-fast computing" and "high-performance computing" are essentially synonyms for "massively-parallel computing."

cs.PF↗

arXiv2011

A Game Theoretical Approach to Broadcast Information Diffusion in Social Networks

One major function of social networks (e.g., massive online social networks) is the dissemination of information, such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to receivers and back (in the form of comments) involves all of the actors considering their knowledge, trust, and popularity, which shape their publishing and commenting strategies. To understand such human aspects of the information dissemination, we propose a game theoretical model of a one-way information forwarding and feedback mechanism in a star-shaped social network that takes into account the personalities of the communicating actors.

cs.SI↗

arXiv2010

A Game Theoretical Approach to Modeling Full-Duplex Information Dissemination

One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the two-way full duplex information forwarding and feedback mechanisms in a social network that take into account the personalities of the communicating actors (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network. The model demonstrates how the emergence of social networks can be explained in terms of maximizing game theoretical utility.

cs.GT↗

arXiv2010

A Game Theoretical Approach to Modeling Information Dissemination in Social Networks

One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the information forwarding and feedback mechanisms in a social network that take into account the personalities of the sender and the receiver (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network.

cs.GT↗