Coordination of people, processes, and artifacts is a significant challenge to successful software engineering that is growing as the scale, distribution, and complexity of software projects grow. This thesis presents an exploratory case study of coordination of interdependent work in a practicing software development team. Qualitative analysis of stakeholder interviews was used to develop nine theoretical propositions that describe coordination behaviours. One proposition was refined by quantitatively exploring the structure of explicit dependencies between work items in relation to their resolution times. Structure measures drawn from social network analysis were used to quantify the structure of explicit dependencies between work items, revealing some lower resolution times were associated with degree centrality measures, but that network structures only explain a small proportion of the variance in resolution times. The results are compared with existing theories of coordination in software engineering and directions for further research are outlined.

In this thesis, I present a framework for bridging the concepts of Social Networks and eLearning Learning Management Systems (LMSs) by finding elements and entities common to both systems, and eliminating these common elements to form an LMS Gadget which can hypothetically be used to extend any Social Network with an API that exposes User and User-Group information so that it also has the functionality of an LMS. I will also include a history of these systems, and a concrete example of such a unification. Finally, I will explore the application of the LMS Gadget to any Web Portal System that exposes User and Group management through an Application Programming Interface (API). This is an application that I conceived of, designed, and did the large majority of the programming for (with assistance on some data access routines to help meet an April 2008 conference deadline). Graphic design was provided by Amos Rowsell of Udutu Learning Systems (a private company for which I have held the role of Lead Developer since November 2005).

Communication is an important activity within software engineering teams as within any other type of organization. In distributed setting, distance has been reported to introduce significant delay in communication. However, new processes and tools have been specifically introduced to alleviate the effect of distance on distributed development. In order to examine if the new processes and tools have indeed made a different on distributed development, we conduct an empirical study in communication of a large globally distributed software engineering team. The goals of our study are to a) investigate the effects of distance on communication speed and b) examine the structure of communication network of this team. We found that distribution does not affect communication speed as reported in previous studies. We also found that this team was able to maintain a project wide communication network with a large core of contributors from across different sites. We conjectured that this structure of communication network helps teams to overcome the challenges of distribution. Finally, we explain the implications of our findings to practitioners and suggest directions for future studies.

This research included male adolescents living on the U.S./Mexico border and the possible effects of a LD and racial and ethnic identification on support seeking behaviour within a bioecological framework. A sample of 34 male Caucasian, Hispanic and Latino students with and without a LD were recruited from two school sites in separate states in the southwest United States. Participants completed a social support questionnaire, selecting support options for managing various life stressors common to adolescents. Research yielded contradicting results from previous explorations of Hispanic and Latino social support behaviours. A one-way ANOVA found no significant differences between the four groups. Independent t-tests clustered students based on racial and ethnic identification with no significant differences. Significant differences were found between LD and non-LD groups in their choice of teachers, with students with a LD being significantly less likely to select teachers for support. In contrast to past research, Caucasian participants were more than twice as likely to select nobody for social support, and less likely to select their parent/guardian, peer/friend, sibling, or teacher for support. Future research should focus on students who are of community and school minority in various contexts across time to gain a more holistic understanding of social support seeking behaviour. / Graduate

In recent years, concerns of privacy have become more prominent for social networks. Anonymizing a graph meaningfully is a challenging problem, as the original graph properties must be preserved as well as possible. We introduce a generalization of the degree anonymization problem posed by Liu and Terzi. In this problem, our goal is to anonymize a given subset of vertices in a graph while adding the fewest possible number of edges. We examine different approaches to solving the problem, one of which finds a degree-constrained subgraph to determine which edges to add within the given subset and another that uses a greedy approach that is not optimal, but is more efficient in space and time. The main contribution of this thesis is an efficient algorithm for this problem by exploring its connection with the degree-constrained subgraph problem. Our experimental results show that our algorithms perform very well on many instances of social network data. / Graduate

Proteins participate in the majority of cellular processes. To determine the function of a protein it is not sufficient to solely know its sequence, its structure in isolation, or how it works individually. Additionally, we need to know how the protein interacts with other proteins in biological networks. This is because most of the proteins perform their main function through interactions. This thesis sets out to improve the understanding of protein-protein interaction networks (PPINs). For this, we propose three approaches: (1) Studying measures and methods used in social and complex networks. The methods, measures, and properties of social networks allow us to gain an understanding of PPINs via the comparison of different types of network families. We studied models that describe social networks to see which models are useful in describing biological networks. We investigate the similarities and differences in terms of the network community profile and centrality measures. (2) Studying PPINs and their role in evolution. We are interested in the relationship of PPINs and the evolutionary changes between species. We investigate whether the centrality measures are correlated with the variability and similarity in orthologous proteins. (3) Studying protein features that are important to evaluate, classify, and predict interactions. Interactions can be classified according to different characteristics. One characteristic is the energy (that is the attraction or repulsion of the molecules) that occurs in interacting proteins. We identify which type of energy values contributes better to predicting PPIs. We argue that the number of energetic features and their contribution to the interactions can be a key factor in predicting transient and permanent interactions. Contributions of this thesis include: (1) We identified the best community sizes in PPINs. This finding will help to identify important groups of interacting proteins in order to better understand their particular interactions. We furthermore find that the generative model describing biological networks is very different from the model describing social networks A generative model is a model for randomly generating observable data. We showed that the best community size for PPINs is around ten, different from the best community size for social and complex network (around 100). We revealed differences in terms of the network community profile and correlations of centrality measures; (2) We outline a method to test correlation of centrality measures with the percentage of sequence similarity and evolutionary rate for orthologous proteins. We conjecture that a strong correlation exists. While not obtaining positive results for our data. Therefore, (3) we investigate a method to discriminate energetic features of protein interactions that in turn will improve the PPIN data. The use of multiple data sets makes possible to identify the energy values that are useful to classify interactions. For each data set, we performed Random Forest and Support Vector Machine with linear, polynomial, radial, and sigmoid kernels. The accuracy obtained in this analysis reinforces the idea that energetic features in the protein interface help to discriminate between transient and permanent interactions. / Graduate / 0984

I dag lider ca 25-35 % av skolungdomar av psykisk ohälsa. Tidigare forskning har visat att denna ohälsa beror på att ungdomar sover alltför lite, vilket i sin tur associerats till en ökad användning av sociala media. Orsakssambanden är emellertid oklara och varierar mellan studier. Av den anledningen genomfördes en enkätstudie på gymnasielever, för att ytterligare belysa hur sambanden ser hos svenska ungdomar. I undersökningen användes två frågeformulär bestående av en reducerad version av KASAM, ett sömnformulär, samt frågor angående sociala media. I studien deltog 51 elever (M: 18.0 år, SD 0.35), varav 22 kvinnliga och 28 manliga elever i ÅK 3. Resultatet visade att cirka hälften av eleverna (49 %) ansåg sig sova signifikant kortare tid än vad de önskade (p<0.0001). De som ansåg sig sova för lite hade även signifikant lägre värden på flera sömnvariabler och hade även signifikant lägre värden på KASAM (p<0.003). Inget säkert samband sågs däremot mellan dessa variabler och uppkoppling på sociala media, även om de kvinnliga studenterna spenderade kortare tid än de manliga eleverna. Sammanfattningsvis bekräftar studien tidigare forskning om kortare sömn hos gymnasieelever och ökad skoltrötthet ger ett sämre psykiskt mående, där kvinnliga elever tenderade att må något sämre än de manliga. Kopplingen till utnyttjandet av sociala media visade på ett positivt samband. Ytterligare studier behövs som på ett mer detaljerat sätt undersöker innehållet i kommunikationen på sociala media och dess eventuella inverkan på sömn och psykisk hälsa.

Industribranschen har idag vissa problem med att attrahera kompetent arbetskraft. Arbetet med att bygga ett starkt Employer Brand har därför blivit allt viktigare. Användandet av sociala medier har ökat och detta skapar nya möjligheter för företag att marknadsföra sig. Frågan är dock om företagen använder denna möjlighet i sitt arbete med Employer Branding. Syftet med denna studie var att undersöka hur industriföretag arbetar med Employer Branding genom sociala medier. Metoden som används för att besvara syftet var kvalitativa intervjuer, med HR-verksamma inom industribranschenen, och en fenomenografisk ansats. Det som eftersöktes var därmed informanternas uppfattning av dessa två fenomen, Employer Branding och sociala medier. Det huvudsakliga resultatet var att de intervjuade företagen visserligen arbetade med Employer Branding, men att endast ett fåtal använde sig av sociala medier. Resursfrågan var den största anledningen till att sociala medier inte användes i den utsträckning informanterna önskade. Nästan samtliga informanter ville och såg ett behov i att användandet av sociala medier skulle öka då det var ett enkelt sätt att nå ut till många på kort tid. Informanterna resonerade även kring risker med sociala medier och vilken information de ville publicera på dessa sidor, något som presenteras närmre i rapporten.

Research: In recent years the concept of crowdfunding, fundraising through social communities, has risen as an alternative for launching new creations and projects. The aim of this study was to explore the non-financial aspects of how interactive value is created through the social networks on a reward-based crowdfunding platform. This was done through investigating how creators on Kickstarter perceive value, approaching the social network from three different levels: the context, structure and practices. This study had a qualitative approach and 13 interviews were performed with key actors on the crowdfunding platform. A secondary study was performed gathering information about Kickstarter through their website. Findings: The result of this study suggests that there are non-financial benefits of being connected with an innovation network. The findings further indicate that the creators are utilizing the digital platforms to gain attention from the crowd and to connect with other networks. The study concludes that collective value is created through interactions on the crowdfunding platform. Further, the general attitude of authenticity within the crowdfunding context implies that the creators’ personal values and motives might play role for the rate success rates of new ventures.

Recent advances in social media have profound technical and economic implications for innovative design. This research is motivated to investigate social network effects on product design with a focus on the interface of engineering design, viral marketing, and social computing. This dissertation envisions a new paradigm of design, called viral product design for social network effects. The research problem is formulated as identification of both an optimal set of product configurations and an optimal set of seed customers so as to maximize product adoption via online social networks through equilibrium solutions to marketing-engineering coordination. Fundamental issues are investigated and a technical framework is proposed with integrated decision-based design methods. Results of case studies demonstrate that the proposed research is able to bridge the gaps between the domains of engineering design and viral marketing by incorporating social network effects. The proposed work is geared towards new design theory and decision models by integrating peer influence of social networks, which shed light on understanding the social aspect of design. The dissertation reveals the fundamental issues underlying viral product design, including the identification of viral attributes, customer preference modeling incorporating subjective experiences, the dynamics of the diffusion mechanism of online social networks, formulation of adoption maximization, and coordination between the marketing and engineering domains. In order to tackle the fundamental issues, a technical framework of viral product design for social network effects is proposed. Accordingly, mathematical and computational models are developed within the framework to support 1) latent customer needs elicitation for viral product attributes extraction, 2) customer preference modeling and quantification for product choice decision making, 3) social network modeling for product adoption prediction, and 4) viral product design evaluation by adoption maximization. These coherent models along the technical framework lay the theoretical foundation of this research, as described below. First, in order to extract potential viral product attributes, latent customer needs elicitation is emphasized. This is because latent customer needs can delight customers unexpectedly, and thus lead to potential product adoption to a large extent. We propose to elicit latent customer needs by use case analogical reasoning from sentiment analysis of online product reviews. A case study of Kindle Fire HD tablets shows the potential and feasibility of the proposed method. The extracted product attributes and attribute levels provide the choice set of viral product attributes. Second, based on the extracted product attributes, a customer preference model based on cumulative prospect theory is presented, accommodating subjective experiences in the product choice decision making process. Moreover, a hierarchical Bayesian model with Markov chain Monte Carlo is used to estimate parameters involved in the model. Based on the case study of aircraft cabin interior design, the model parameters under different experimental conditions show systematic influence of subjective experiences in choice decision making. Furthermore, a copula structure is used to construct a holistic product utility, showing customers' overall preferences to a product. This measure is crucial to product choice decision making in the context of social networks. Third, in order to predict product adoption incorporating peer influence of social networks, a linear threshold-hurdle model is proposed. It overcomes multiple drawbacks of traditional diffusion models by modeling activation thresholds, influence probability, adoption spread, holistic utility of the product, and hurdle utility of a customer in a holistic fashion. A case study of Kindle Fire HD tablets demonstrates both the predictive power of the proposed model and interesting results about customers' adoption behavior. This model paves the way for product adoption maximization in large social networks. Fourth, in order to coordinate between marketing-engineering concerns, I formulate a bi-level game theoretic optimization model for viral product design evaluation, in which the leader maximizes product adoption, while the follower optimizes product line performance. Through social network effects in terms of viral product attributes and viral influence attributes, the expected number of product adopters and the expected shared surplus, resulting from the identified product configurations and seed customers, are proved to be larger than those obtained from existing practice of viral marketing and product line design respectively, based on the case study of Kindle Fire HD tablets. Thus, the proposed paradigm of design extends the traditional boundaries among domains of engineering design, viral marketing, and social computing.