Node discovery in a networked organization

In this paper, I present a method to solve a node discovery problem in a networked organization. Covert nodes refer to the nodes which are not observable directly. They affect social interactions, but do not appear in the surveillance logs which record the participants of the social interactions. Discovering the covert nodes is defined as identifying the suspicious logs where the covert nodes would appear if the covert nodes became overt. A mathematical model is developed for the maximal likelihood estimation of the network behind the social interactions and for the identification of the suspicious logs. Precision, recall, and F measure characteristics are demonstrated with the dataset generated from a real organization and the computationally synthesized datasets. The performance is close to the theoretical limit for any covert nodes in the networks of any topologies and sizes if the ratio of the number of observation to the number of possible communication patterns is large

Digital Marketing for Sustainable Growth: Business Models and Online Campaigns Using Sustainable Strategies

t: In recent years, digital marketing has transformed the way in which companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the Internet has given rise to new business models based on the bidirectionality of communication between companies and Internet users. Digital marketing, new business models, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies have started to see the digital ecosystem as not only their present, but also as their future. From this long-term perspective, companies are concerned about sustainability and the growth of their business models. There are new business models on the Internet that support social causes, new platforms aimed at supporting social and sustainable projects, and digital advertising campaigns promoting sustainability. The overarching aim of this Special Issue was to analyze the development of these new strategies as well as their influence on the sustainability of digital marketing strategies. Therefore, we aimed to analyze how companies adopt these new technologies in a digital environment that is increasingly concerned with the sustainability of business models and actions on the Internet

Transnational Activism in Support of National Protest: Questions of Identity and Organization

This article considers the question of whether transnational activism supporting national protest attains a cohesive collective identity on social media whilst organizationally remaining localized. It examines a corpus of social media data collected in the course of two months of rolling protests in 2013 against the largest proposed open-cast gold mine at Roşia Montană, Romania, which echoed among Romanian expatriates. A network text analysis of the data supplemented with interview findings revealed concerns with protest logistics as common across the transnational networks of protest localities on both Facebook and Twitter, a finding that testified to the coordinated character of the protests. On the other hand, collective identity emerged as the fruit of attempts to surmount localized protest experiences of geographically disparate but civically-minded social media users

Inferring Social Status and Rich Club Effects in Enterprise Communication Networks

Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels --- voice call, short message, and email --- to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a "rich club" maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.Comment: 13 pages, 4 figure

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Most of the studied networks are based on the co-authorship of software artefacts defined at the level of files, modules, or packages. While this approach has led to insights into the social aspects of software development, it neglects detailed information on code changes and code ownership, e.g. which exact lines of code have been authored by which developers, that is contained in the commit log of software projects. Addressing this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. This information allows us to construct directed, weighted, and time-stamped networks, where a link signifies that one developer has edited a block of source code originally written by another developer. Our tool is applied in case studies of an Open Source and a commercial software project. We argue that it opens up a massive new source of high-resolution data on human collaboration patterns.Comment: MSR 2019, 12 pages, 10 figure