Twitter-archive und die Herausforderungen von "Big Social Data" für die Medien- und Kommunikationswissenschaft

Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

How does enterprise social media help retail employees innovate?

An increasing number of organizations have installed enterprise social media (ESM) platforms to allow employees to collaborate, work independently, and to innovate more easily. While research has started to explain how such technologies can lead to improved collaboration and productivity, their role in assisting employees in innovation processes remains unclear. In our research-in-progress we examine the case of a global retail organization that adopted ESM for all employees with the view to foster employee-driven innovation. We report on our on-going data collection and analysis, in which we focus on the salient mechanisms and contingency factors why ESM under some conditions facilitates employee-driven innovation and why under some conditions it does not. We report on on-going data collection, data analysis strategies and emergent findings, and conclude with a brief outlook on our future research strategies.

Students’ well-being and social connections

Description of Workshop/Poster Presentation This presentation will showcase CORE Connections – ‘Creating Opportunities for Resilience and Engagement’ – which is a whole-school approach to mental health promotion. While initially designed to prevent adolescent depression and substance abuse, current thinking suggests that competency enhancement (e.g., autonomy, competence, supportive networks) more widely improves students’ well-being, educational engagement, and learning outcomes. In the presentation, we will provide an overview of the CORE project, describe the CORE intervention, which is conceptualized as a dynamic and penetrating process of social practices, present some preliminary findings from the pilot phase of CORE, and conclude our presentation with an interactive section with the participants. This project will highlight a wellness focus that addresses social engagement within whole school cultures. Purpose of the Presentation Student mental and physical well-being has gained increasing attention. Our presentation will introduce the CORE project, which has a potential to decrease student depression, anxiety, and substance use, and to increase student self-esteem and learning outcomes. In this vein, our presentation will raise the public awareness of the salient role of social connection in student well-being. Specifically, a group of presenters will discuss the impact of social connection on students’ anxiety, mathematics achievement, and perceived racial discrimination. • We will present participants with an alternative way to conceptualize and approach mental health promotion within a school context. In contrast to prescribed programs that are commonly used in today’s schools, CORE is a whole-school approach that is flexibly integrated into all aspects of the classroom and school environment. Our aim is to illustrate the intervention principles of CORE while highlighting examples of mental health outcomes/transformation. • Underutilized in mental health promotion research, social network analysis provides critical information in understanding relationships between social cohesion (e.g., a student’s connectedness to others) and mental health outcomes. This session will showcase how focusing on and strengthening social connections in and out of school can contribute to student well-being, achievement, and mental health. Educational Objectives By the end of the presentation, participants will • obtain a general overview of the CORE program, • understand how psychological health and school performance relate to student well-being, • and understand how social connections in and out of school can contribute to student well-being. Interactive / Participatory Component We will invite audience members to discuss inhibitors and contributors to student well-being and the best ways for schools to help students feel safe, connected, and valued. Presentation Key Points • Overview of the CORE project • Theorization of social connection • Some empirical studies emerging from CORE • Presenter-audience interaction Evidence of Relevance and Utility to Participants Potential participants are adults with significant relationships with students, either as family members, community neighbors, educators, scholars, service providers, or policy makers. Our presentation will inspire these significant adults to construct a welcoming society to help improve student well-being.

Second language social networks and communication-related acculturative stress: The role of interconnectedness

Although a substantial amount of cross-cultural psychology research has investigated acculturative stress in general, little attention has been devoted specifically to communication-related acculturative stress (CRAS). In line with the view that cross-cultural adaptation and second language (L2) learning are social and interpersonal phenomena, the present study examines the hypothesis that migrants’ L2 social network size and interconnectedness predict CRAS. The main idea underlying this hypothesis is that L2 social networks play an important role in fostering social and cultural aspects of communicative competence. Specifically, higher interconnectedness may reflect greater access to unmodified natural cultural representations and L2 communication practices, thus fostering communicative competence through observational learning. As such, structural aspects of migrants’ L2 social networks may be protective against acculturative stress arising from chronic communication difficulties. Results from a study of first generation migrant students (N = 100) support this idea by showing that both inclusiveness and density of the participants’ L2 network account for unique variance in CRAS but not in general acculturative stress. These results support the idea that research on cross-cultural adaptation would benefit from disentangling the various facets of acculturative stress and that the structure of migrants’ L2 network matters for language related outcomes. Finally, this study contributes to an emerging body of work that attempts to integrate cultural/cross-cultural research on acculturation and research on intercultural communication and second language learning.

Anatomy of a trending topic : Methods for the visualisation of retweet chains [Anatomie eines Trending Topics: Methoden zur Visualisierung von Retweet-Ketten]

Twitter and other social networking sites play an ever more present role in the spread of current events. The dynamics of information dissemination through digital network structures are still relatively unexplored, however. At what time an issue is taken up by whom? Who forwards a message when to whom else? What role do individual communication participants, existing digital communities or the technical foundations of each network platform play in the spread of news? In this chapter we discuss, using the example of a video on a current sociopolitical issue in Australia that was shared on Twitter, a number of new methods for the dynamic visualisation and analysis of communication processes. Our method combines temporal and spatial analytical approaches and provides new insights into the spread of news in digital networks. [Social media dienen immer häufger als Disseminationsmechanismen für Medieninhalte. Auf Twitter ermöglicht besonders die Retweet-Funktion den schnellen und weitläufgen Transfer von Nachrichten. In diesem Beitrag etablieren neue methodische Ansätze zur Erfassung, Visualisierung und Analyse von Retweet-Ketten. Insbesondere heben wir hervor, wie bestehende Netzwerkanalysemethoden ergänzt werden können, um den Ablauf der Weiterleitung sowohl temporal als auch spatial zu erfassen. Unsere Fallstudie demonstriert die verbreitung des videoclips einer am 9. Oktober 2012 spontan gehaltenen Wutrede der australischen Premierministerin Julia Gillard, in der sie Oppositionsführer Tony Abbott als Frauenhasser brandmarkte. Durch die Erfassung von Hintergrunddaten zu den jeweiligen NutzerInnen, die sich an der Weiterleitung des Videoclips beteiligten, erstellen wir ein detailliertes Bild des Disseminationsablaufs im vorliegenden Fall. So lassen sich die wichtigsten AkteurInnen und der Ablauf der Weiterleitung darstellen und analysieren. Daraus entstehen Einblicke in die allgemeinen verbreitungsmuster von Nachrichten auf Twitter].

Measuring source credibility of social engineering attackers on Facebook

Past research has suggested that social networking sites are the most common source for social engineering-based attacks. Persuasion research shows that people are more likely to obey and accept a message when the source’s presentation appears to be credible. However, many factors can impact the perceived credibility of a source, depending on its type and the characteristics of the environment. Our previous research showed that there are four dimensions of source credibility in terms of social engineering on Facebook: perceived sincerity, perceived competence, perceived attraction, and perceived worthiness. Because the dimensionalities of source credibility as well as their measurement scales can fluctuate from one type of source to another and from one type of context to another, our aim in this study includes validating the existence of those four dimensions toward the credibility of social engineering attackers on Facebook and developing a valid measurement scale for every dimension of them.

How information around acute events comes into being on social media?

In this digital age, as social media is emerging as a central site where information is shared and interpreted, it is essential to study information construction issues on social media sites in order to understand how social reality is constructed. While there is a number of studies taking an information-as-objective point of view, this proposed study emphasizes the constructed and interpretive nature of information and explores the processes through which information surrounding acute events comes into being on micro-blogs. In order to conduct this analysis systematically and theoretically, the concept of interpretive communities will be deployed. This research investigates if or not micro-blog based social groups can serve as interpretive communities, and, if so, what role might they play in the construction of information, and the social impacts that may arise. To understand how this process is entangled with the surrounding social, political, technical contexts, cases from both China (focusing on Sina Weibo) and Australia (focusing on Twitter) will be analysed.

Language and Letters of the Bluestocking Network : Sociolinguistic Issues in Eighteenth Century Epistolary English

This study deals with language change and variation in the correspondence of the eighteenth-century Bluestocking circle, a social network which provided learned men and women with an informal environment for the pursuit of scholarly entertainment. Elizabeth Montagu (1718 1800), a notable social hostess and a Shakespearean scholar, was one of their key figures. The study presents the reconstruction of Elizabeth Montagu s social networks from her youth to her later years with a special focus on the Bluestocking circle, and linguistic research on private correspondence between Montagu and her Bluestocking friends and family members between the years 1738 1778. The epistolary language use is investigated using the methods and frameworks of corpus linguistics, historical sociolinguistics, and social network analysis. The approach is diachronic and concerns real-time language change. The research is based on a selection of manuscript letters which I have edited and compiled into an electronic corpus (Bluestocking Corpus). I have also devised a network strength scale in order to quantify the strength of network ties and to compare the results of the linguistic research with the network analysis. The studies range from the reconstruction and analysis of Elizabeth Montagu s most prominent social networks to the analysis of changing morphosyntactic features and spelling variation in Montagu s and her network members correspondence. The linguistic studies look at the use of the progressive construction, preposition stranding and pied piping, and spelling variation in terms of preterite and past participle endings in the regular paradigm (-ed, - d, -d, - t, -t) and full / contracted spellings of auxiliary verbs. The results are analysed in terms of social network membership, sociolinguistic variables of the correspondents, and, when relevant, aspects of eighteenth-century linguistic prescriptivism. The studies showed a slight diachronic increase in the use of the progressive, a significant decrease of the stigmatised preposition stranding and increase of pied piping, and relatively informal but socially controlled epistolary spelling. Certain significant changes in Elizabeth Montagu s language use over the years could be attributed to her increasingly prominent social standing and the changes in her social networks, and the strength of ties correlated strongly with the use of the progressive in the Bluestocking Corpus. Gender, social rank, and register in terms of kinship/friendship had a significant influence in language use, and an effect of prescriptivism could also be detected. Elizabeth Montagu s network ties resulted in language variation in terms of network membership, her own position in a given network, and the social factors that controlled eighteenth-century interaction. When all the network ties are strong, linguistic variation seems to be essentially linked to the social variables of the informants.

Life events and social support among patients with major depressive disorder

The study is part of a research project of 269 psychiatric patients with major depression, Vantaa Depression Study, in the Department of Mental Health and Alcohol Research of the National Public Health Institute and the Department of Psychiatry of the Peijas Medical Care District. The aim was to study at the onset of MDE psychosocial differences in subgroups of patients and clustering of events into time before depression and its prodromal phase, to study whether more severe life events and less social support predict poorer outcome in all patients, but most among those currently in partial remission, whether social support declines as a consequence of time spent in MDE, is sensitive to improvement, and whether social support is influenced by neuroticism and extraversion. After screening, a semistructured interview (SCAN, version 2.0) was used for the presence of DSM-IV MDE, and other psychiatric diagnoses. Life events and social support were studied with semistructured methods (IRLE, Paykel 1983; IMSR, Brugha et al. 1987), perceived social support and neuroticism/extraversion with questionnaires (PSSS-R, Blumenthal et al. 1987; EPI, Eysenck and Eysenck 1964) at baseline, 6 and 18 months. At the onset of depression life events were common. No major differences between subgroups of patients were found; the younger had more events, whereas those with comorbid alcoholism and personality disorders perceived less support. Although events were distributed evenly between the time before depression, the prodromal phase and the index MDE, two thirds of the patients attributed their depression to some life event. Adversities and poor perceived support influenced the outcome of all psychiatric patients, most in the subgroup of full remission. In the partial remission group, the impact of severe events and in the MDE, perceived support was important. Low objective and subjective support were predicted by longer time spent in MDE. Along with improvement subjective support improved. Neuroticism and extraversion were associated with the size of social network and perceived support and predicted change of perceived support. In conclusion, adversities were common in all phases of depression. They may thus have many roles; before depression they may precipitate it, in the prodromal phase worsen symptoms, and during the MDE, the outcome of depression. Patients often attributed their depression to a life event. Psychosocial subgroup differences were quite small. Perceived support predicted the outcome of depression, and time spent in MDE objective and subjective support. Neuroticism and extraversion may modify the level and change particularly in perceived support, thereby indirectly effecting vulnerability to depression.

Editorial of "International Journal of Critical Indigenous Studies Volume 6, Number 2, 2013"

The International Journal of Critical Indigenous Studies (IJCIS) now complements the recently launched National Indigenous Research and Knowledges Network (NIRAKN) in its efforts to build Indigenous research capacity. In this context the journal provides a platform for the research of Indigenous postgraduates, early- to mid-career researchers, and senior scholars. Indigenous scholars are therefore encouraged to submit their articles to future editions of the IJCIS, an ‘Excellence in Research for Australia’ (ERA) ranked journal.

Using enterprise social networks as innovation platforms

Do enterprise social network platforms in an organization make the company more innovative? In theory, through communication, collaboration, and knowledge exchange, innovation ideas can easily be expressed, shared, and discussed with many partners in the organization. Yet, whether this guarantees innovation success remains to be seen. The authors studied how innovation ideas moved--or not--from an enterprise social network platform to regular innovation processes at a large Australian retailer. They found that the success of innovation ideas depends on how easily understandable the idea is on the platform, how long it has been discussed, and how powerful the social network participants are in the organization. These findings inform management strategies for the governance of enterprise social network use and the organizational innovation process.

Social Networks and Everyday Practices in Russia

My doctoral dissertation in sociology and Russian studies, Social Networks and Everyday Practices in Russia, employs a "micro" or "grassroots" perspective on the transition. The study is a collection of articles detailing social networks in five different contexts. The first article examines Russian birthdays from a network perspective. The second takes a look at health care to see whether networks have become obsolete in a sector that is still overwhelmingly public, but increasingly being monetarised. The third article investigates neighbourhood relations. The fourth details relationships at work, particularly from the vantage point of internal migration. The fifth explores housing and the role of networks and money both in the Soviet and post-Soviet era. The study is based on qualitative social network and interview data gathered among three groups, teachers, doctors and factory workers, in St. Petersburg during 1993-2000. Methodologically it builds on a qualitative social network approach. The study adds a critical element to the discussion on networks in post-socialism. A considerable consensus exists that social networks were vital in state socialist societies and were used to bypass various difficulties caused by endemic shortages and bureaucratic rigidities, but a more debated issue has been their role in post-socialism. Some scholars have argued that the importance of networks has been dramatically reduced in the new market economy, whereas others have stressed their continuing importance. If a common denominator in both has been a focus on networks in relation to the past, a more overlooked aspect has been the question of inequality. To what extent is access to networks unequally distributed? What are the limits and consequences of networks, for those who have access, those outside networks or society at large? My study provides some evidence about inequalities. It shows that some groups are privileged over others, for instance, middle-class people in informal access to health care. Moreover, analysing the formation of networks sheds additional light on inequalities, as it highlights the importance of migration as a mechanism of inequality, for example. The five articles focus on how networks are actually used in everyday life. The article on health care, for instance, shows that personal connections are still important and popular in post-Soviet Russia, despite the growing importance of money and the emergence of "fee for service" medicine. Fifteen of twenty teachers were involved in informal medical exchange during a two-week study period, so that they used their networks to bypass the formal market mechanisms or official procedures. Medicines were obtained through personal connections because some were unavailable at local pharmacies or because these connections could provide medicines for a cheaper price or even for free. The article on neighbours shows that "mutual help" was the central feature of neighbouring, so that the exchange of goods, services and information covered almost half the contacts with neighbours reported. Neighbours did not provide merely small-scale help but were often exchange partners because they possessed important professional qualities, had access to workplace resources, or knew somebody useful. The article on the Russian work collective details workplace-related relationships in a tractor factory and shows that interaction with and assistance from one's co-workers remains important. The most interesting finding was that co-workers were even more important to those who had migrated to the city than to those who were born there, which is explained by the specifics of Soviet migration. As a result, the workplace heavily influenced or absorbed contexts for the worker migrants to establish relationships whereas many meeting-places commonly available in Western countries were largely absent or at least did not function as trusted public meeting places to initiate relationships. More results are to be found from my dissertation: Anna-Maria Salmi: Social Networks and Everyday Practices in Russia, Kikimora Publications, 2006, see www.kikimora-publications.com.

Multidimensionality of Actors in Business Networks: The Influence of Social Action in Pharmacy Networks in Finland

In the markets-as-networks approach business networks are conceived as dynamic actor structures, giving focus to exchange relationships and actors’ capabilities to control and co-ordinate activities and resources. Researchers have shared an understanding that actors’ actions are crucial for the development of business networks and for network dynamics. However, researchers have mainly studied firms as business actors and excluded individuals, although both firms and individuals can be seen as business actors. This focus on firms as business actors has resulted in a paucity of research on human action and the exchange of intangible resources in business networks, e.g. social exchange between individuals in social networks. Consequently, the current conception of business networks fails to appreciate the richness of business actors, the human character of business action and the import of social action in business networks. The central assumption in this study is that business actors are multidimensional and that their specific constitution in any given situation is determined by human interaction in social networks. Multidimensionality is presented as a concept for exploring how business actors act in different situations and how actors simultaneously manage multiple identities: individual, organisational, professional, business and network identities. The study presents a model that describes the multidimensionality of actors in business networks and conceptualises the connection between social exchange and human action in business networks. Empirically the study explores the change that has taken place in pharmaceutical retailing in Finland during recent years. The phenomenon of emerging pharmacy networks is highly contemporary in the Nordic countries, where the traditional license-based pharmacy business is changing. The study analyses the development of two Finnish pharmacy chains, one integrated and one voluntary chain, and the network structures and dynamics in them. Social Network Analysis is applied to explore the social structures within the pharmacy networks. The study shows that emerging pharmacy networks are multifaceted phenomena where political, economic, social, cultural, and historical elements together contribute to the observed changes. Individuals have always been strongly present in the pharmacy business and the development of pharmacy networks provides an interesting example of human actors’ influence in the development of business networks. The dynamics or forces driving the network development can be linked to actors’ own economic and social motives for developing the business. The study highlights the central role of individuals and social networks in the development of the two studied pharmacy networks. The relation between individuals and social networks is reciprocal. The social context of every individual enables multidimensional business actors. The mix of various identities, both individual and collective identities, is an important part of network dynamics. Social networks in pharmacy networks create a platform for exchange and social action, and social networks enable and support business network development.

A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks

Our study concerns an important current problem, that of diffusion of information in social networks. This problem has received significant attention from the Internet research community in the recent times, driven by many potential applications such as viral marketing and sales promotions. In this paper, we focus on the target set selection problem, which involves discovering a small subset of influential players in a given social network, to perform a certain task of information diffusion. The target set selection problem manifests in two forms: 1) top-k nodes problem and 2) lambda-coverage problem. In the top-k nodes problem, we are required to find a set of k key nodes that would maximize the number of nodes being influenced in the network. The lambda-coverage problem is concerned with finding a set of k key nodes having minimal size that can influence a given percentage lambda of the nodes in the entire network. We propose a new way of solving these problems using the concept of Shapley value which is a well known solution concept in cooperative game theory. Our approach leads to algorithms which we call the ShaPley value-based Influential Nodes (SPINs) algorithms for solving the top-k nodes problem and the lambda-coverage problem. We compare the performance of the proposed SPIN algorithms with well known algorithms in the literature. Through extensive experimentation on four synthetically generated random graphs and six real-world data sets (Celegans, Jazz, NIPS coauthorship data set, Netscience data set, High-Energy Physics data set, and Political Books data set), we show that the proposed SPIN approach is more powerful and computationally efficient. Note to Practitioners-In recent times, social networks have received a high level of attention due to their proven ability in improving the performance of web search, recommendations in collaborative filtering systems, spreading a technology in the market using viral marketing techniques, etc. It is well known that the interpersonal relationships (or ties or links) between individuals cause change or improvement in the social system because the decisions made by individuals are influenced heavily by the behavior of their neighbors. An interesting and key problem in social networks is to discover the most influential nodes in the social network which can influence other nodes in the social network in a strong and deep way. This problem is called the target set selection problem and has two variants: 1) the top-k nodes problem, where we are required to identify a set of k influential nodes that maximize the number of nodes being influenced in the network and 2) the lambda-coverage problem which involves finding a set of influential nodes having minimum size that can influence a given percentage lambda of the nodes in the entire network. There are many existing algorithms in the literature for solving these problems. In this paper, we propose a new algorithm which is based on a novel interpretation of information diffusion in a social network as a cooperative game. Using this analogy, we develop an algorithm based on the Shapley value of the underlying cooperative game. The proposed algorithm outperforms the existing algorithms in terms of generality or computational complexity or both. Our results are validated through extensive experimentation on both synthetically generated and real-world data sets.