The present thesis aims to deduce tasks and characteristics of end users during the open innovation process on the social web. The social web with its communities, forums and blogs affords new prospects as well as unknown challenges for companies, and at the same has increasingly influenced academic research during the last few years. Especially research regarding communication behaviour on the social web as well as social web technologies has currently progressed well. However, in innovation research, social web technologies are currently primarily used to integrate users into the company’s innovation process, for example through company user toolkits or company innovation communities. In those cases users were excluded from their normal social web environment and integrated into a company’s environment, a sort of laboratory environment. Despite this, the present research project will use the natural behaviour, comments and discussions of users within their social web environment to develop and apply a new mixed-method approach with the aim to deduce tasks and characteristics of innovative end users on the social web. To apply the mixed-method approach within a longitudinal case study and to deduce statements and regularities regarding the innovation process on the social web, it was possible to analyse the end user developer online forum of one of the leading open source CRM software technologies. Based on this analysis, the assumptions from an extensive literature analysis could be verified and extended: it could be shown that the expected single innovative user does not exist. In fact, the process from the initial idea to an innovation requires different users with different characteristics and different points of view. They will be deduced, explained and presented within the present thesis.

The UK is required to reduce its greenhouse gas emissions by 80 per cent from 1990 levels, by 2050. Greenhouse gas emissions attributed to the UK higher education sector have increased by 34.5 per cent from 1990 to 2005. Higher education institutions have a unique role in the UK greenhouse gas emissions inventory, beyond management of their own estates and compliance with policy and legislation, higher education institutions have responsibilities as innovators and educators, inspiring students and employees through example and best practice. This study sought to understand acceptability of greenhouse gas emissions reduction policies among employees of a higher education institution. The value-belief-norm theory was used in a questionnaire to understand individual attitudinal factors thought to influence policy acceptability (N=405). Recognising that an employee's attitudinal factors may be influenced by their work colleagues, this study used social network analysis to understand the social context within which individual attitudinal factors sit. Support was found for higher education institutions to reduce their greenhouse gas emissions. Employees found policies that encouraged desired behaviours, such as assistance with train travel costs and working from home, to be more acceptable than policies that discouraged undesired behaviours, such as doubling the price of a car-parking permit. Support was found for the structure and content of the value-belief-norm theory, but logistic regression suggested that it provided a weak explanation of employee policy acceptability, indicating that other factors may have a greater role. Analysis of workplace social networks suggested that employees have small social groups (x̄=8) and do not select to be close to colleagues that reflect their own perspectives. Practitioners and policymakers should seek to address this void in environmental social norms through recruitment of more environmental champions to deliver strong and persuasive pro-environmental messages.

The innovation ecosystem’s online presence continues to grow with the emergence and maturation of ICT-based platforms. With these new channels, a diversity of actors, including firms, scientists, universities, media entities, and individuals, interact to satisfy their information needs and to access and mobilize network-based resources. This research is among a growing number of social science studies examining the advent of social media and its influence on the innovation process, asking, “How do different types of actors use social media to form network linkages, and what kinds of innovative outcomes will result?” To study this complex network activity, I turn to Twitter, the popular microblogging service, and focus on the case of graphene, a novel nanotechnology material consisting of a two-dimensional sheet of carbon atoms. Twitter is one of the world’s most often-used social networks, boasting over 500 million users (200+ million active). Graphene, on the other hand, is a relatively well-bounded area of scientific inquiry with ongoing, concurrent scientific and commercialization activity. The primary sample dataset derives from 34 graphene firms’ friend and followers relationships captured in early 2014. Nine interview transcripts supply qualitative data. The results show that network formation on Twitter is not random and that certain actor relationships predict following linkages. A series of network visualizations show that users agglomerate in communities; these communities exhibit greater density than the larger ecosystem network and a propensity to congeal in topically focused ways. That is, each community indicates a coherent topical focus, suggesting that graphene firms follow specific sets of users in ways that support their information and resource needs. At the micro-level, an unstructured text mining approach to operationalizing and computing information distance shows that increasing amounts of topical distance between any two users decreases the likelihood of a tie existing. Are innovation outcomes more likely to occur in strategically-developed and information-rich social media networks? Drawing on different sources of “behavioral additionality” – or changes in behaviors as a result of social media participation – I identify ex-ante several such plausible outcomes, which could include increased awareness, improved problem solving ability, community development, and greater sales. The qualitative results show that social media participation results in increased awareness of graphene and related ecosystem topics, but engagement is a key tactical maneuver that actors pursue, often in varying ways, to access and mobilize other resources. Policy implications are targeted at intermediary institutions and scientists, while management implications focus on high-technology SMEs. Limitations include alternative theories to explaining social media participation and engagement, methodological issues, and the continuing evolution of social media platforms and usage patterns. Future work is considered to address the temporal nature of network construction and topical growth (or constriction), as well as the ability to map areas of science and technology through social media data.

This dissertation uses a relational approach and a contentious politics framework to examine the archaeological record. Methodologically, it merges spatial and social network analyses to promote a geosocial archaeology. Combined, the articles create a counter-narrative that highlights how environmentally focused investigations fail to explain how and why societies in the Southwest often reorganize horizontally. The first article uses geosocial networks, which I argue represent memory maps, to reveal that the socially important, and sophisticated, act of forgetting was employed by people in the Gallina region during A.D. 1100 - 1300. A concomitant community level, settlement pattern analysis demonstrates similarities between the arrangement of Gallina and Basketmaker-era settlements. These historically situated settlement structures, combined with acts of forgetting, were used by Gallina region residents to institute and maintain a horizontally organized social movement that was likely aimed at rejecting the hierarchical social atmosphere in the Four Corners region. The second article proposes that as ideologically charged material goods are consumed, fissures within past ideological landscapes are revealed and that these fissures can demonstrate acts of resistance in the archaeological past. It also contends that social and environmental variables need to be combined for these conflicting religious and political practices to be correctly interpreted. The third article applies many of the ideas outlined in the second article to a case study in the Greater Southwest during A.D. 1200 - 1450. Fractures in the ideological landscape demonstrate that the Salado Phenomenon was a religious social movement formed around, and successful because of, its populist nature. Based on variations in how the Salado ideology interacted with contemporaneous hierarchical and non-hierarchical religious and political organizations it is probable that the Salado social movement formed around desires for the open access to religious knowledge.

Job seekers and employers frequently make application and selection decisions based on how well they believe there is a ‘fit’ with the organization and job. The personenvironment fit literature has strongly supported this practice demonstrating that fit is an antecedent to attraction, selection, and attrition. What has been lacking, however, is evidence that once individuals enter the organization their fit relates to performance. Using a social network analytical lens, I develop a framework that integrates PE fit and social networks to explore antecedents to employee performance. Using this framework, I explore how informal workplace relationships may act as catalysts through which fit either enhances or detracts from individual performance, how fit might directly influence performance once the social context is taken into account, and how fit might make an individual an attractive exchange partner benefiting performance. Results suggest that PE fit is related to individual performance (both in- and extra-role) but that this relationship differs depending on how well embedded the employee is in the informal social networks of the organization. It is only when accounting for the ‘who you know’ element of organizational life that we can see how ‘who you are’ relates to performance.

Resource mobilization theory and political opportunity theory are often used to describe separate portions of social movements. This dissertation proposes a combined model of these two theoretical perspectives which describes how social movement organizations effectively engage in social marketing both online and offline. The field of social marketing highlights the utility of standard commercial marketing practices to achieve non-commercial goals. I argue that, while commercial marketing practices may benefit social movement organizations and are more cost effective given emerging technology, momentum for gathering resources, will be stifled unless a political opportunity presents itself. Guided by theory about the ways that political opportunities are translated into action by organizations, and momentum acquired through mobilizing resources, cycles of opportunity and resulting resource responses by housing social movement organizations are examined over time to present a case study for this theoretical model. The seemingly endless cycle of resource gathering underscores organizational mobilization of resources as a process rather than an outcome. My model outlines numerous forces that shape an organization’s ability to mobilize in two distinct ways, through resources deployed (online and offline) and resources gathered. Resources will be discussed in three categories: organizational characteristics, network structure/position, and media/Internet presence. The relative importance of these factors and this process are described at length in the review of theoretical literature and will be illustrated in the case study that I provide: the housing social movement. Data for this case study has been collected through hyperlink network analysis, general webometrics, and congressional archives. My research aims to provide suggestions for the strategic socio-technical networking and social marketing of social movement organizations.

This paper provides insights on how five different frames of the Edward Snowden issue (Hero, Patriot, Traitor, Whistleblower, Dissident) have been diffused on the Twitter platform. This study uses NodeXL to collect, analyze and visualize all the tweets including the keyword “Edward Snowden” from February 17 to April 10, 2014 to examine the flow of information and the interaction between opinion leaders along with the characteristics of opinion leaders in this specific issue. Findings provide insight about future strategic communication for general branding and public image maintenance. / text

Despite the fact that swidden agriculture has been the subject of decades of research, questions remain about the extent to which it is constrained by demographic growth and if it can adapt to environmental limits. In this dissertation I analyze ethnographic and ethnohistorical evidence from the Toledo District, Belize, and suggest that Q'eqchi' Maya swidden agriculture may be more ecologically adaptive than previously thought. I use social network analysis to examine farmer labor exchange networks from a chronosequence of five villages where swidden is used. Results suggest that changes in land-use patterns, network structure, and reciprocity rates may increase the system's resilience to changes in the forest's agricultural productivity. I develop a novel interpretation of labor reciprocity that highlights how unreciprocated exchanges, when they occur within the context of a social network, may limit overexploitation of a common property resource. These results are then interpreted in the context of panarchy theory; I suggest that the structural variability observed in labor exchange networks may explain how Q'eqchi' swidden maintains its identity under changing environmental conditions - a definition of resilience. Thus, the resulting picture of Q'eqchi' swidden is one of socioecological resilience rather than homeostasis; dynamic labor exchange networks help maintain a village's social cohesion, ultimately limiting pioneer settlements and slowing overall rates of deforestation. A historical and demographic analysis of market incursions into southern Belize supports this conclusion.

社會網路分析（social network analysis）將社會關係以網路形式表示，從原本純粹分析社會互動的工具，到近年來被廣泛被應用在社會學、組織研究、資訊科學、生物學、語言學等各種領域，藉由引入數學圖學理論與與日益精進的電腦處理能力，使得社會網路分析能從有別於以往的角度找出個體間行動的規律；而詞義相似度（word similarity）是資訊檢索等技術發展的基礎課題之一，近年來對詞義相似度的量測有許多方法的提出。 本研究針對英語字詞利用社會網路分析這樣的工具，藉由提出不同的網路建構方式，以語料庫為資料來源，設定網路節點與連結關係，以共現網路（co-occurrence networks）為基礎，經由改變產生與篩選的條件，觀察以社會網路分析已有的性質或指標做調整，是否可以對詞義相似度提供另一種量測方式；同時以目前詞義相似度研究上已有同義詞標準評比對前述產生的網路與所計算的性質做驗證，並進一步探討使用社會網路分析在詞義相似度研究上的適用性。

The study of social network dynamics has become an increasingly important component of many disciplines in the social sciences. In the past decade, statistical models and methods have been proposed which permit researchers to draw statistical inference on these dynamics. This thesis builds on one such family of models, the stochastic actor oriented model (SAOM) proposed by Snijders [2001]. Goodness of fit for SAOMs is an area that is only just beginning to be filled in with appropriate methods. This thesis proposes a Mahalanobis distance based, Monte Carlo goodness of fit test that can depend on arbitrary features of the observed network data and covariates. As remediating poor fit can be a difficult process, a modified model distance (MMD) estimator is devised that can help researchers to choose among a set of model elaborations. In practice, panel data is typically used to draw SAOM-based inference. This thesis also proposes a score-type test for time heterogeneity between the waves in the panel that is computationally cheap and fits into a convenient, forward model selecting workflow. Next, this thesis proposes a rigorous method for aggregating so-called relational event data (e.g. emails and phone calls) by extending the SAOM family to a family of hidden Markov models that suppose a latent social network is driving the observed relational events. Finally, this thesis proposes a measurement model for SAOMs inspired by error-in-variables (EiV) models employed in an array of disciplines. Like the relational event aggregation model, the measurement model is a hidden Markov model extension to the SAOM family. These models allow the researcher to specify the form of the mesurement error and buffer against potential attenuating biases and other problems that can arise if the errors are ignored.