Do social networks bridge political divides? The analysis of VKontakte social network communication in Ukraine

New electronic forms of political communication have become increasingly popular in countries with weak democratic institutions. The effectiveness of these new forms of association in altering political behavior, however, remains uncertain even in developed democratic regimes. This paper investigates connections between regional variation in electoral behavior and regional distribution of electronic social networks in the case of Ukraine's polarized and institutionally unstable democracy. Our analysis of online networks shows that, somewhat contrary to conventional wisdom, electronic communication does not bridge political divides. This finding casts doubt on the effectiveness of online for…

ICO Crowdfunding: Incentives, Pricing Strategy, Token Strategy and Crowd Involvement

AbstractBlockchain technologies provide means to develop services that are secure, transparent and efficient by nature. Unsurprisingly, the emerging business opportunities has gained a lot of interest that is realized in form of successful Initial Coin Offerings (ICOs) that are able to raise billions of USD through crowdfunding campaign. In this exploratory research we study 91 ICOs through content analysis in order to investigate the special characteristics of ICO crowdfunding as business models towards the possible investors. We found that ICOs can be described through (1) the model for providing incentives for investment, (2) the pricing strategy, (3) the token strategy and (4) the activ…

The Spanning Tree based Approach for Solving the Shortest Path Problem in Social Graphs

Nowadays there are many social media sites with a very large number of users. Users of social media sites and relationships between them can be modelled as a graph. Such graphs can be analysed using methods from social network analysis (SNA). Many measures used in SNA rely on computation of shortest paths between nodes of a graph. There are many shortest path algorithms, but the majority of them suits only for small graphs, or work only with road network graphs that are fundamentally different from social graphs. This paper describes an efficient shortest path searching algorithm suitable for large social graphs. The described algorithm extends the Atlas algorithm. The proposed algorithm so…

Analysing the presence of school-shooting related communities at social media sites

Surprisingly cruel mass murders and attacks have been witnessed in the educational institutions of the Western world since the 1970s. These are often referred to as 'school shootings'. There have been over 300 known incidents around the world and the number is growing. Social network sites (SNSs) have enabled the perpetrators to express their views and intentions. Our result is that since about 2005, all major school shooters have had a presence in SNS and some have left traces that would have made possible to evaluate their intentions to carry out a rampage. A further hypothesis is that future school shooters will behave in a similar manner and would thus be traceable in the digital sphere…

Detection of Fake Profiles in Social Media - Literature Review

Revealing Fake Profiles in Social Networks by Longitudinal Data Analysis

Multitask deep learning for native language identification

Identifying the native language of a person by their text written in English (L1 identification) plays an important role in such tasks as authorship profiling and identification. With the current proliferation of misinformation in social media, these methods are especially topical. Most studies in this field have focused on the development of supervised classification algorithms, that are trained on a single L1 dataset. Although multiple labeled datasets are available for L1 identification, they contain texts authored by speakers of different languages and do not completely overlap. Current approaches achieve high accuracy on available datasets, but this is attained by training an individua…

Violent Conflict and Online Segregation: An Analysis of Social Network Communication Across Ukraine's Regions

Does the intensity of a social conflict affect political division? Traditionally, social cleavages are seen as the underlying cause of political conflicts. It is clear, however, that a violent conflict itself can shape partisan, social, and national identities. In this paper, we ask whether social conflicts unite or divide the society by studying the effects of Ukraine's military conflict with Russia on online social ties between Ukrainian provinces (oblasts). In order to do that, we collected original data on the cross-regional structure of politically relevant online communication among users of VKontakte social networking site. We analyze the panel of provinces spanning the most active p…

Identifying Images with Ladders Using Deep CNN Transfer Learning

Deep Convolutional Neural Networks (CNNs) as well as transfer learning using their pre-trained models often find applications in image classification tasks. In this paper, we explore the utilization of pre-trained CNNs for identifying images containing ladders. We target a particular use case, where an insurance firm, in order to decide the price for workers’ compensation insurance for its client companies, would like to assess the risk involved in their workplace environments. For this, the workplace images provided by the client companies can be utilized and the presence of ladders in such images can be considered as a workplace hazard and therefore an indicator of risk. To this end, we e…

User Influence and Follower Metrics in a Large Twitter Dataset

A modelling framework for social media monitoring

This paper describes a hierarchical, three-level modelling framework for monitoring social media. Immediate social reality is modelled through the first level of the models. They represent various virtual communities at social media sites and adhere to the social world models of the sites, i.e., the "site ontologies". The second-level model is a temporal multirelational graph that captures the static and dynamic properties of the first-level models from the perspective of the monitoring site. The third-level model consists of a temporal relational database scheme that models the temporal multirelational graph within the database. The models are specified and instantiated at the monitoring s…

Gaming Bot Detection: A Systematic Literature Review

In online games, some players employ programs (bots) that allow them to bypass game routines and effortlessly gain virtual resources. This practice leads to negative effects, such as reduced revenue for the game development companies and unfair treatment for ordinary players. Bot detection methods act as a counter measure for such players. This paper presents a systematic literature review of bot detection in online games. We mainly focus on games that allow resource accumulation for players between game sessions. For this, we summarize the existing literature, list categories of games ignored by the scientific community, review publicly available datasets, present the taxonomy of detection…

Understanding Fast Diffusion of Information in the Social Media Environment. A Comparison of Two Cases.

The purpose of this paper is to gain understanding of what factors cause rapid issue spread in social media, to help predict issue growth. The frequency graphics of two issues, Arctic Sunrise and U.S. capitol shooting, were compared to investigate rapidity of spread on Twitter. Next, a qualitative model was applied to explain the differences found. Furthermore, a first attempt was made to investigate issue transfer between social media and news media. The findings showed that news items and tweets were interrelated, with hardly any time-lag in between, although the tweets continued longer and included more emotion. The approach seems promising but needs further testing. When in practice mon…

Tracing Potential School Shooters in the Digital Sphere

There are over 300 known school shooting cases in the world and over ten known cases where the perpetrator(s) have been prohibited to perform the attack at the last moment or earlier. Interesting from our point of view is that in many cases the perpetrators have expressed their views in social media or on their web page well in advance, and often also left suicide messages in blogs and other forums before their attack, along the planned date and place. This has become more common towards the end of this decennium. In some cases this has made it possible to prevent the attack. In this paper we will look at the possibilities to find commonalities of the perpetrators, beyond the fact that they…

Principles of social media monitoring and analysis software

Online Stakeholder Interaction of Some Airlines in the Light of Situational Crisis Communication Theory

Part 2: Digital Marketing and Customer Relationship Management; International audience; The purpose of this paper is to explore the participation of main actors in Facebook. The engagement shows different degrees of participation that directly affect the brand image and reputation. This research applies Situational Crisis Communication Theory (SCCT) to interaction in the social media. It provides possibilities for decision makers to monitor diverse messages online, understand stakeholder concerns and reply to them adequately, which is especially important in crisis situations. Seven airline organizations were selected for a comparative analysis concerning their online discussions. The verif…

Exploring social media network landscape of post-Soviet space

The “post-Soviet space” consists of countries with a substantial fraction of the world’s population; however, unlike many other regions, its social media network landscape is still somewhat under-explored. This paper aims at filling this gap. To this purpose, we use anonymized data on user friendships at VK.com (also known as VKontakte and, informally, as “Russian Facebook”), which is the largest and most popular social media portal in the post-Soviet space with hundreds of millions of user accounts. Using the VK network snapshots from October 2015 to December 2016, we conduct a “multiscale” empirical study of this network by considering conn…

A Survey on Technologies Which Make Bitcoin Greener or More Justified

According to recent estimates, one bitcoin transaction consumes as much energy as 1.5 million Visa transactions. Why is bitcoin using so much energy? Most of the energy is used during the bitcoin mining process, which serves at least two significant purposes: a) distributing new cryptocurrency coins to the cryptoeconomy and b) securing the Bitcoin blockchain ledger. In reality, the comparison of bitcoin transactions to Visa transactions is not that simple. The amount of transactions in the Bitcoin network is not directly connected to the amount of bitcoin mining power nor the energy consumption of those mining devices; for example, it is possible to multiply the number of bitcoin transactio…

Graph-based exploration and clustering analysis of semantic spaces

Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …

Distributed evolutionary approach to data clustering and modeling

In this article we describe a framework (DEGA-Gen) for the application of distributed genetic algorithms for detection of communities in networks. The framework proposes efficient ways of encoding the network in the chromosomes, greatly optimizing the memory use and computations, resulting in a scalable framework. Different objective functions may be used for producing division of network into communities. The framework is implemented using open source implementation of MapReduce paradigm, Hadoop. We validate the framework by developing community detection algorithm, which uses modularity as measure of the division. Result of the algorithm is the network, partitioned into non-overlapping co…

Identity Use and Misuse of Public Persona on Twitter

Social media sites have appeared during the last 10 years and their use has exploded all over the world. Twitter is a microblogging service that has currently 320 million user profiles and over 100 million daily active users. Many celebrities and leading politicians have a verified profile on Twitter, including Justin Bieber, president Obama, and the Pope. In this paper we investigate the '‘hundreds of Putins and Obamas phenomenon’ on Twitter. We collected two data sets in 2015 containing 582 and 6477 profiles that are related to the G20 leaders’ profiles on Twitter. The number of namesakes varied from 5 to 1000 per leader. We analysed in detail various aspects of the Putin and Erdogan rela…

Analysis of Viral Advertisement Re-Posting Activity in Social Media

More and more businesses use social media to advertise their services. Such businesses typically maintain online social network accounts and regularly update their pages with advertisement messages describing new products and promotions. One recent trend in such businesses’ activity is to offer incentives to individual users for re-posting the advertisement messages to their own profiles, thus making it visible to more and more users. A common type of an incentive puts all the re-posting users into a random draw for a valuable gift. Understanding the dynamics of user engagement into the re-posting activity can shed light on social influence mechanisms and help determine the optimal incentiv…

Collective Behavior of Price Changes of ERC-20 Tokens

We analyze a network constructed from tokens developed on Ethereum platform. We collect a large data set of ERC-20 token prices; the total market capitalization of the token set is 50.2 billion (109) US dollars. The token set includes 541 tokens; each one of them has a market capitalization of 1 million US dollars or more. We construct and analyze the networks based on cross-correlation of tokens’ returns. We find that the degree distributions of the resulting graphs do not follow the power law degree distribution. We cannot find any hierarchical structures nor groupings of ERC-20 tokens in our analysis. peerReviewed

Online activity traces around a "Boston bomber"

This paper describes traces of user activity around a alleged online social network profile of a Boston Marathon bombing suspect, after the tragedy occurred. The analyzed data, collected with the help of an automatic social media monitoring software, includes the perpetrator's page saved at the time the bombing suspects' names were made public, and the subsequently appearing comments left on that page by other users. The analyses suggest that a timely protection of online media records of a criminal could help prevent a large-scale public spread of communication exchange pertaining to the suspects/criminals' ideas, messages, and connections.

Network-based indices of individual and collective advising impacts in mathematics

AbstractAdvising and mentoring Ph.D. students is an increasingly important aspect of the academic profession. We define and interpret a family of metrics (collectively referred to as “a-indices”) that can potentially be applied to “ranking academic advisors” using the academic genealogical records of scientists, with the emphasis on taking into account not only the number of students advised by an individual, but also subsequent academic advising records of those students. We also define and calculate the extensions of the proposed indices that account for student co-advising (referred to as “adjusted a-indices”). In addition, we extend some of the proposed metrics to ranking universities a…

Neural Networks with Multidimensional Cross-Entropy Loss Functions

Deep neural networks have emerged as an effective machine learning tool successfully applied for many tasks, such as misinformation detection, natural language processing, image recognition, machine translation, etc. Neural networks are often applied to binary or multi-class classification problems. In these settings, cross-entropy is used as a loss function for neural network training. In this short note, we propose an extension of the concept of cross-entropy, referred to as multidimensional cross-entropy, and its application as a loss function for classification using neural networks. The presented computational experiments on a benchmark dataset suggest that the proposed approaches may …

Cross-Social Network Collaborative Recommendation

Online social networks have become an essential part of our daily life, and an increasing number of users are using multiple online social networks simultaneously. We hypothesize that the integration of data from multiple social networks could boost the performance of recommender systems. In our study, we perform cross-social network collaborative recommendation and show that fusing multi-source data enables us to achieve higher recommendation performance as compared to various single-source baselines.

Utilitarian Use of Social Media Services - A Study on Twitter

This paper applies structuration theory (ST) and service dominant logic (SDL) as lenses to study different uses of information systems (IS). We argue that resources provided by IS may be combined and reproduced by appropriating them for different purposes than the design purposes of the IS. The study provides empirical data and analysis to showcase the use of resources for utilitarian purposes in the context of social media services (SMS). Through an analysis of sponsored tweets on Twitter, we show that users employ implicit and explicit resources for utilitarian outcomes. Our findings imply that users create their own service through appropriation of resources available in the social conte…

A Mobile Healthcare System for Sub-saharan Africa

The disparity between healthcare systems in developed countries and underdeveloped countries is huge, particularly due to the fact that the healthcare infrastructure of former is based on a sophisticated technological infrastructure. Efforts are being made worldwide to bridge this disparity and make healthcare services affordable even to the most remote areas of undeveloped countries. Recent growth of mobile networks in underdeveloped countries argues for building mHealth systems and applications on their basis. However, peculiarities of the area introduce difficulties into potential use cases of mobile devices, thus making the copying of mHealth services from developed countries inapplicab…

A Generic Architecture for a Social Network Monitoring and Analysis System

This paper describes the architecture and a partial implementation of a system designed for the monitoring and analysis of communities at social media sites. The main contribution of the paper is a novel system architecture that facilitates long-term monitoring of diverse social networks existing and emerging at various social media sites. It consists of three main modules, the crawler, the repository and the analyzer. The first module can be adapted to crawl different sites based on ontology describing the structure of the site. The repository stores the crawled and analyzed persistent data using efficient data structures. It can be implemented using special purpose graph databases and/or …

Recommending Serendipitous Items using Transfer Learning

Most recommender algorithms are designed to suggest relevant items, but suggesting these items does not always result in user satisfaction. Therefore, the efforts in recommender systems recently shifted towards serendipity, but generating serendipitous recommendations is difficult due to the lack of training data. To the best of our knowledge, there are many large datasets containing relevance scores (relevance oriented) and only one publicly available dataset containing a relatively small number of serendipity scores (serendipity oriented). This limits the learning capabilities of serendipity oriented algorithms. Therefore, in the absence of any known deep learning algorithms for recommend…

A Repository for Multirelational Dynamic Networks

Nowadays, WWW contains a number of social media sites, which are growing rapidly. One of the main features of social media sites is to allow to its users creation and modification of contents of the site utilizing the offered WWW interfaces. Such contents are referred to as user generated contents and their type varies from site to site. Social media sites can be modeled as constantly evolving multirelational directed graphs. In this paper we discuss persistent data structures for such graphs, and present and analyze queries performed against the structures. We also estimate the space requirements of the proposed data structures, and compare them with the naive "store each complete snapshot…

Sampled Fictitious Play on Networks

We formulate and solve the problem of optimizing the structure of an information propagation network between multiple agents. In a given space of interests (e.g., information on certain targets), each agent is defined by a vector of their desirable information, called filter, and a vector of available information, called source. The agents seek to build a directed network that maximizes the value of the desirable source-information that reaches each agent having been filtered en route, less the expense that each agent incurs in filtering any information of no interest to them. We frame this optimization problem as a game of common interest, where the Nash equilibria can be attained as limit…

Oikeuttamisverkostot : miten analysoida julkisissa keskusteluissa esitettyjen oikeutusten keskinäisiä suhteita

Luc Boltanskin ja Laurent Thévenot'n vuonna 1991 kehittämä teoria toiminnan moraalisesta oikeuttamisesta on yksi keskeisistä Pierre Bourdieun jälkeisen "pragmatistisen" sosiologian saavutuksista. Tässä artikkelissa esitetään Boltanskin ja Thévenot'n oikeuttamisteoriaan sekä Eeva Luhtakallion ja Tuomas Ylä-Anttilan kehittämään julkisen oikeuttamisen analyysiin (JOA) perustuva metodi, joka havainnollistaa ja visualisoi moraalisen oikeuttamisen kategorioiden verkostoitumista. Artikkelissa metodia havainnollistetaan New York Timesin ilmastokeskustelua koskevan aineiston avulla, mutta sitä voidaan soveltaa kaikkiin julkisia kiistoja koskeviin tekstiaineistoihin. Se voidaan mieltää diskurssiverko…

What Key Aspects Do ICOs Reveal About Their Businesses?

AbstractBlockchain technologies disrupt industries by enabling decentralized and transactional data sharing across a network of untrusted participants, among others. Initial Coin Offerings (ICOs) are a novel form of crowdfunding through which hundreds of blockchain-enabled businesses manage to raise billions of dollars in total only in United States. However, there is a lack of understanding of the ICO phenomenon especially related to the business aspects. In this paper, we describe the results of an exploratory study of 91 ICOs and identify the key business model elements that ICOs reveal in their websites and whitepapers. Furthermore, we also note the immaturity and lack of transparency o…

Seed Activation Scheduling for Influence Maximization in Social Networks

This paper addresses the challenge of strategically maximizing the influence spread in a social network, by exploiting cascade propagators termed “seeds”. It introduces the Seed Activation Scheduling Problem (SASP) that chooses the timing of seed activation under a given budget, over a given time horizon, in the presence/absence of competition. The SASP is framed as a blogger-centric marketing problem on a two-level network, where the decisions are made to buy sponsored posts from prominent bloggers at calculated points in time. A Bayesian evidence diffusion model – the Partial Parallel Cascade (PPC) model – allows the network nodes to be partially activated, proportional to their accumulat…

Engagement as a Driver of Growth of Online Health Forums: Observational Study

Background: The emerging research on nurturing the growth of online communities posits that it is in part attributed to network effects, wherein every increase in the volume of user-generated content increases the value of the community in the eyes of its potential new members. The recently introduced metric engagement capacity offers a means of quantitatively assessing the ability of online platform users to engage each other into generating content; meanwhile, the quantity engagement value is useful for quantifying communication-based platform use. If the claim that higher engagement leads to accelerated growth holds true for online health forums (OHFs), then engagement tracking should be…