The introduction of a new idea: How the term ‘intentionality’ has spread within the scientific discourse
Robert Ullrich | FU Berlin | Germany
In the middle of the 20th century, psychology went through a so called ‘cognitive revolution’. The ‘revolution’ was driven by an increase in rejections of overtly behaviouristic descriptions of behaviour. Cognitive psychologists introduced or re-introduced a number of new terms to psychology to further enable reference to inner, non-observable mental capacities. The current case study is to track and reconstruct the introduction and distribution of one such term: ‘intentionality’. The term was introduced to cross-species comparative psychology during the 1970’s. Since then, the term plays a major role in explaining communicative behaviours in human and non-humans. In this study, the aim is to perform a citation network analysis on approximately 1000 journal articles involved in the ‘animal communication discourse’ to quantify the spread of the term and to answer the following questions: Which publications become hub statuses and which roles do theoretical articles without actual data have (e.g. narrative reviews) within a citation map? The articles will be rated by their content as ‘supportive’, ‘neutral’, or ‘opposite’ with regard to the finding of ‘intentionality’ in the respective study subject. On account of that procedure it is asked: Which results are cited more frequently? Do research groups produce throughout positive or throughout negative evidence on a topic and, if so, what are possible reasons for that? By answering these questions, the network analysis will not make judgements about the truthfulness of a certain topic. Rather, it aims to visualise the spread of new information within a social network, and it tries to identify potential subjective influences on scientific practice in general.
Using twitter data networks to investigate italian constitutional referendum campaign
Francesco Santelli | University of Naples Federico II | Italy
The development of online social media is having significant effects on the contemporary political dynamics.
In Italy, while in previous years the politicians relied on tradition mass media sources, during last constitutional referendum, that took place in December, 4th 2016, the debate between the two opposite factions arose strongly on social networks, such as Twitter.
From a Twitter network based dataset, it is possible to detect most popular hashtags related to referendum topics, then, it is possible to identify two distinct classes of users: for and against the referendum proposal.
The hashtags choice for the first phase (#bastaunsi, #iovotosi and #iovotono, #iodicono), in order to web-scrape only the twitters related the referendum campaign, is made both taking into account the literature reviews and the analysis of the occurrences, leading to a one-mode, weighted and undirected network. The hashtags play the role of the nodes, and the co-occurrences are the weights of the links between hashtags.
The purpose is firstly to figure out which ones were the most important Twitter influencer topics of the campaign for the "Yes" and for the "No" by analyzing the hashtags that marked strongly the two fields.
After that, a community detection analysis is performed be means of the Fast Greedy algorithm, that is a fast implementation of the Newman-Girvan algorithm, one of the first community detection algorithm to be used in social networks field that uses as objective function to maximize the modularity of the network in each step. Nodes belonging to the same community will result to be strongly related each other compared to the rest of the network.
From thousands of hashtags for each camp and from millions of links between them, due to the community detection algorithm the hashtags are contracted in clusters. For the “yes” camp are detected 9 communities, for the “no” camp the communities are instead 13.
Analyzing the hashtags that are present in each community, is possible to give them a common topic/field of reference, to understand which political parties and which politicians are the most important actors inside the network.
For the “yes” side, 5 clusters are sharing the strong influence of Matteo Renzi and of the Democratic Party (“PD”), showing the center-left side and its leader as the most important center of gravity of this faction. Other groups are instead related to a grey area of not clear opinion about the vote.
On the other hand, an higher degree of heterogeneity is showed for the “no” camp, with Movimento 5 Stelle that is by far the most represented political force. Both the right side headed by Silvio Berlusconi and the hard-left side play a subordinate role.
In both networks several cluster are strongly related with television programs and election speeches, showing that the twitter campaign moved with a certain degree of interconnection with other traditional ways of lead an election contest.
Drawing a Map of Mixed Methods Approaches to Social Network Analysis
Dominik Froehlich | University of Vienna | Austria
Social network analysis and multiple and mixed method research are two important methodological trends across disciplines (Bolíbar, 2015; Domínguez & Hollstein, 2014; Edwards, 2010). The increased usage of combinations of both—what we call mixed methods approaches to social network analysis (MMSNA)—has proliferated a plethora of approaches and designs. Since MMSNA are rather resource-intensive (Froehlich & Harwood, 2016), a guide for researchers is needed of how methods of social network analysis may be combined effectively and efficiently. In this poster presentation, we use social network analysis as a tool to review the usage of MMSNA in one domain of research (education and learning). We create a map that informs about the potential of mixing and integrating multiple types of data and multiple types of methods of analysis. Furthermore, this map is a tool that contributes to the objective of making the method more accessible also for researchers with more limited resources. This is done by moving away from typologies derived from theory that "have become almost too refined" (Bryman, 2006, p. 98) and staying close to research practice.
Data is generated through a systematic literature review across journals of the domain. For the selected articles, we code the methods used for data collection and analysis. The temporal order of the methods is then used to build a relational dataset. At the time of writing, the data collection and analysis is ongoing, the final dataset will be ready as of April 2017. Quantitative social network analysis is used to analyze the relational dataset created. We analyze the network map that shows how different methods are linked with each other by extracting three centrality measures: indegree, outdegree, betweenness. Here, for instance, methods high in indegree may hint at a potential for preceding component preparation methods (Schoonenboom & Froehlich, 2016). Depicting a network graph and the network measures associated with it (e.g., measures of centrality) offer more versatile ways of finding and discussing patterns in previous research than typologies or mere counts of certain methods used (e.g., Bryman, 2006).
In conclusion, we use techniques of social network analysis to provide a map of how MMSNA designs were implemented in previous empirical research. This can trigger an informed debate about what designs have proven to be useful, informs about the variety of potential designs, the ways of integrating qualitative and quantitative methods in social network research, and how to achieve the research goals given economic constraints. Furthermore, next to just reviewing what has been done and what not, the social network analysis used as a review tool allows the identification of new approaches to mixing quantitative and qualitative methods.
A genealogy of the Brazilian research in freshwater fishery from its Academic Social Network
Carlos Viegas | USP - Universidade de São Paulo | Brazil
Keywords: Genealogy, Social Network Analysis, Fishery
The objective of this work is to describe how in Brazil the network of researches interested in freshwater fishery has evolved since the 1980 years until now, based on a data collection of the academic linkage between supervisors to graduate students.
This data survey should result in a genealogy, which allows finding the “foundation fathers” of the Brazilian research into freshwater fishery and their academic descendants as well as the main branches of this scientific field in the country.
The data source for determinate the relation of academic supervision is the “Lattes Plataform” (Plataforma Lattes), a huge repository maintained by the Brazil´s Research National Council (Conselho Nacional de Pesquisa – CNPq) which gathers thousands of Curricula Vitae (“CV Lattes”) of Brazilian researchers into digital records, available by internet, containing for each individual information like: employment; academic origin; published articles; supervision activities; participation in scientific events; etc.
From these CV Lattes it is possible to extract data of interest for analysis and to build a graphical tree describing de supervision relations of this academic field in Brazil.
Initially, the analysis is made by means of the tabulation of the data extracted from the CVs, followed by the production of graphs in order to determine the genealogical tree (academic “father / mother” to “descendants’) and too see how these links could form “clusters” of academic kinship. At this point is possible to apply graph theory analysis to find some centrality figures into the network showing the most relevant “foundation fathers”.
To identify in the field the researchers positioned as “fathers” for having generated a significant academic heritage, allows finding the branches of investigative interest transmitted from supervisor to student, making up the division of the whole scientific field into specific research zones with their own objects. These objects of interest should permit building criteria suitable to gather the CVs Lattes into diverse groups and to show the whole profile of the Brazilian freshwater fishery research.
Another step of the analysis should apply tools of Network Social Analysis in order to find the internal degree of collaboration among researchers by means of their collaboration as authors in publishing in academic journals.
As result of this work, it should produce a kind of phylogenic of the Brazilian freshwater fishery research showing, in a general manner, how it has evolved and trends of its development. This could cast some light to see if the “research area” named by funding institutions match with the social network built by the relation supervisor / student, or not.
Entangled θιασῶται in the Greek colonies of the Black Sea Area (3rd c BC – 3rd c AD)
Annamaria - Izabella Pazsint | Babes-Bolyai University | Romania
Professional associations, networks
The poster has as goal to present a case study on how Social Network Analysis can be applied to the field of ancient history, and to pinpoint some of its benefits. The focus will be the private professional associations coming from the Greek colonies of the Black Sea area (3rd c BC – 3rd c AD), and more particularly the networks created both on the inside of these associations, as well as on their outside. These networks will illustrate the linkage between members and their proximal or distant entourage.
The poster will have as starting point a specific prosopographical dataset, collected in the last months in an online database (http://romans1by1.com/). All the evidence comes from epigraphic sources.
Under focus will be all the individuals attested in connection to private professional associations. By this I mean that not only the members will be analysed, but also the „non-members”, respectively family members, elite members, as well as lower social categories, all the individuals which interact with these „groups”. Basically all social interactions will be monitored in order to distinguish the social clusters which emerge, and in order to point the possible predilections which these associations might have in developing relations with certain categories (and the other way round, in order to show what type of social categories have an interest in being so visibly interlinked with members of private professional associations).
Through this poster it is also intended to observe what the local characteristics are, especially considering the fact that the area is not defined by political or economic uniformity (important aspects which might lead to different networking habits). In this respect, an example might be relevant: in the Bosporan Kindgdom, some of the few private professional associations include among its members important representatives of the Royal court, which is not the case, for example, at Tomis (obviously reference is not made to Royal functionaries in this case, but as analogy, to Imperial ones). Identifying an existing pattern of social network is expected, considering the already interpreted data, pattern which will be nuanced through this endeavour.
For the visualisation and exploration part, the software Gephi will be used.
How interns learn interprofessional collaboration at the workplace: a network perspective
Janneke Witte | UMC Utrecht | Netherlands
How interns learn interprofessional collaboration at the workplace: a network perspective
Keywords: workplace based learning, interprofessional collaboration, social network analysis
With the increasing complexity of modern health care, health issues can often not be solved by one discipline or health care professional alone. Therefore, it is important that students learn interprofessional collaboration (IPC) during medical training to prepare them for future practice.
The clerkships provide opportunities for workplace learning, which is often informal and spontaneous. This work-based learning is essential for interprofessional education and is thought to be connected with the work that professionals undertake in collaboration in the workplace. Interaction in the workplace and professional networks are considered to be related to spontaneous learning in collaboration. Openness to experience is another asset for workplace learning, as students who are open to experience exhibit more intellectual curiosity and goal orientation, which is assumed to support workplace learning.
In other fields of educational science, scholars have demonstrated the importance and power of social networks in the development of professionals at the workplace. Social network analysis, therefore, may help understand IPC learning of students during clerkships.
The aim of this study is to contribute to a better understanding of how students learn interprofessional collaboration in the workplace to further connect this learning to formal education programs in curricula.
• During the GP clerkship, how do interns perceive key characteristics of their network with professionals who deliver interprofessional patient care?
• How do key network characteristics of interns differ between interns who are open to experience from those who are not?
We will interview 20 interns during their rotation in general practice using a semi-structured approach. To gain insight into their egocentric network, we will ask them to elaborate on the people/professionals they perceive to be part of their network and the frequency and duration of the contacts they have with these people. With this information, we will look into three key characteristics of the networks: 1. Size of network, 2. Strength of ties, and 3. similarity between ties
Moreover, we will ask the interns what situations in daily practice they value as opportunities to learn how to deliver interprofessional patient care. Openness to experience will be measured by the amount and diversity of situations the intern recognises in daily practice to be valuable for learning IPC.
The interview data will be quantified to perform a social network analysis of the three formerly mentioned key characteristics of the networks. Similarity will be measured by the level of education and kind of function besides gender and age.
Subsequently, we will use a multilevel analysis to compare the networks of the different participants. We will divide the students according to the amount and diversity of the situation they mention from which they can learn to deliver interprofessional care.
This study design is approved by the ethical review board, and the interviews will be conducted in April-June 2017. In September we hope to be able to present the first preliminary results.
Ego-networks of novice teachers: a key aspect for improving their professional development
Susana López Solé | Ramon Llull University | Spain
keywords: social capital, social network analysis, novice teachers
This study examines the social side of novice teachers and draws on Social Network Analysis (SNA) to explore the relation between the social capital of novice teachers and their professional development. Social capital is generally defined as the resources embedded in social networks, resources that can be accessed or mobilized across the network through a purposive action (Lin, 1999). The concept of social capital in this study is considered as a multidimensional concept (Liou & Daly, 2014; Nahapiet & Ghoshal, 1998): structural (pattern of ties), relational (quality of ties) and cognitive (shared communications). An ego-net participatory mapping (Kahn, & Antonucci, 1980) was applied to 10 novice teachers to analyse the personal networks of novice teachers inside the school. In order to capture the structural aspect, participants were asked to provide the names of other teachers regarding the networks advice, need to vent, ideas, material, friendship, influence and practices, and place them in the circles around them (the more important in terms of closeness or frequency, the closer to the center of the circle). Moreover, the egocentric social network data was entered and analysed using EgoNet (McCarty, 2003), a software program for personal networks. This method was combined with qualitative semi-structured interviews to understand the meaning and importance of their relations. These interviews were also employed to provide informational data on the relational and cognitive aspects of social capital. Therefore, a mixed-method design was implemented to perform a triangulation in order to better understand the social capital of novice teachers regarding their professional development. Findings allow us to understand the relationship between aspects of the cohort’s social network and professional development of novice teachers and demonstrate the importance of considering informal interactions inside the school. Different studies suggest the importance of teacher collaboration networks for building teacher capacity and student achievement (Moolenaar, Daly, & Sleegers, 2010; Penuel, Riel, Krause, & Frank, 2009). Social networks in teachers’ professional development can also provide professional support and opportunities to share knowledge, thereby fostering collaborative norms of interactions and diminishing teacher isolation (Baumard & Starbuck, 2005; Collinson & Cook, 2004).
Nash equilibrium with knowledge externality in students’ collaboration network
Yuliya Skoblova | National Research university Higher School of Economics | Russian Federation
Key words: Nash equilibrium, knowledge externality, peer effect
We study collaboration of students in one of the Russian universities. The aim of the paper is to verify theoretical results of model (Matveenko and Korolev, 2016) which analyses behavior in social network in framework of Nash equilibrium in a network game with production and knowledge externalities. In the model, each agent has initial stock of a good (it may be time) that can be consumed or invested into knowledge (partly or totally). Knowledge is used in production of goods for consumption in the second period. The volume of production depends both on personal investments of the agent and her ‘environment’. The environment is modeled as the sum of personal and neighbours’ investments into knowledge. The results of the theoretical model allow us to formulate hypotheses to be checked empirically.
We construct two types of networks for the same group of students: one represents friendship relationships and another one reflects interactions of students concerning only studying process (mutual help). Regression analysis is used to identify correlation between node’s position (in- and out- degree-centrality) in two networks. ERGM-model that describes the process of ties formation is created. It includes network structure characteristics (density, clustering, reciprocity, etc.) and personal characteristics of students (homophily, popularity, activity).
Models help to identify students who produce and distribute knowledge externality in the network (those who has the most influence on their peers). We find that there is a case of “presence of productivity”, when the raise of received externality reduces personal investments of the agent (negative peer effect). Correspondingly, a free-rider problem takes place: low achievers get help from others and stop making efforts themselves. Analysis of the two networks together shows that there’s a cycle (Matthew effect). High achievers get popularity in both networks, and their own investments in knowledge grow, while low achievers (those who ask for help a lot) make efforts for developing friendship ties to widen their opportunities to ask for help. In result, their own investments into knowledge go down. We assess accuracy of the theoretical model.
Defining r/The_Donald and r/ChangeMyView: An examination of the roles of moderators and users in the norm-setting of online communities
Ella Guest | University of Manchester | United Kingdom
keywords: social media, community norm development, text analysis
Online communities often have the freedom, and responsibility, to define their own community norms. The social news site Reddit is an example of a platform that imposes no editorial control over content produced. Reddit’s administers instead encourage users to create topic-based forums, called subreddits, according to their own desires and to develop unique standards of acceptable behaviours. A small number of community members who volunteer as moderators together with the wider community of non-moderating contributors work to define the purpose and tone of their subreddits, and detail a code of conduct for participating in the space. These developments are made both implicitly and explicitly and can highlight irreconcilable desires within the community. As such Reddit makes a fascinating subject of study for gaining understanding of the techniques and methods members and moderators of online communities use in the delicate process of norm-setting.
This research is in the early stages of defining the theoretical and methodological considerations required in researching the processes of norm-setting by subreddit communities. I am currently piloting this work by studying two distinct subreddits; r/The_Donald - a community for ardent supporters of Donald Trump - and r/ChangeMyView – a forum where users actively encourage others to try to change their opinions on any given topic. The research uses social network analysis techniques to identify changes in the respective networks of r/The_Donald and r/ChangeMyView moderators over time, determining the presence of distinct moderation eras. It is hypothesised that these moderation eras will correspond with different eras of community norms and standards. Text analysis techniques are then used to examine whether shifts in the moderator network correspond to shifts in the informal community discussions and formal moderator controlled standards of behaviour – i.e. the implicit and explicit sources of community norms on r/The_Donald and r/ChangeMyView.
What are Genosociograms and How Can We Generate, Analyze, and Interpret them? Theoretical and Applied Perspectives on the Network of Relationships
Holger von der Lippe | MSB Medical School Berlin | Germany
This poster depicts the possible blending of genograms and sociograms into a unified and variable tool for the collection, visualization, and analysis of relationship contexts. Shared perspectives on personal relationships by genograms and sociograms are highlighted and integrative concepts from the literature are presented. My proposal is, then, to conceptualize both family and non-family relations as genosociograms and to analyze them as egocentric (personal) networks of relationships. This is illustrated by the example of the (non-clinical) case of the genosociogram of a student. The network analysis of her genosociogram reveals several interesting insights into the differential centrality of people in her network, into differences of the relationship structure across different network sectors, and into the particular relationship constellations of her network members. The consequences and chances of genosociograms for clinical casework and systemic theorizing are discussed in the concluding section of the article.
Drawing sociograms is not quite like drawing graphs: Evaluating the use of touchscreen participant-aided sociograms
Bernie Hogan | University of Oxford | United Kingdom
In this paper we discuss the design decisions and the evaluation of Network Canvas, a novel touch screen interface for the capture of personal networks. While Network Canvas is currently in use in several studies, we focus on RADAR, a longitudinal study of young men who have sex with men (YMSMs) and in particular the first wave. In this work we ask whether Network Canvas is considered usable, efficient and accurate. We also ask what features inform the layout of the networks and in particular whether attributes of the nodes are relevant over and beyond what is captured by the graph topology.
Like most participant-aided sociograms, RADAR includes a name generator, a step for arranging ties on a field (in our case concentric circles, or a ‘bullseye’ diagram), a step for denoting indirect ties as edges, and steps for collecting edge and alter data. Some of the participants in RADAR were recruited from a previous study that used a whiteboard-based tool thereby allowing a within subjects comparison of tool performance and alter generation.
Using data from the log and the resulting network, we test a number of claims related to network drawing and expectations from social network analysis. For example, we hypothesize that individuals arrange their ties such that people socioemotionally closer to ego are closer to the centre of the bullseye (even without explicit prompting). We also demonstrate how individuals do not abide by many of the standard metrics from the graph drawing community (such as minimising edge crossings). Instead, respondents appear more focused on representing latent information from the relationship between ego and alter. The latent information (closeness, role, geography) warps the graph layout in ways that are intelligible to the respondent and signal important information. Respondents still abide by expectations for components less than edges.
We believe the attribute-mediated layout of a sociogram is an important methodological insight that should be preserved in future designs. These attributes indicate that ego has a commitment to the fidelity of the graph and the accuracy of the information given. We further believe that the ability to see the whole personal network at once reinforces ego’s commitment to this accuracy in comparison to other myopic methods (particularly the dyad census). We provide future claims to be tested in subsequent longitudinal work with the same data set.
Peer-effects and organizational performance in interorganizational networks: A longitudinal study
Anna Piazza | University of Greenwich | United Kingdom
The notion of peer effects is receiving increased attention in organizational network research. However, how peer effects actually operate and spread between organizations remains unclear. What structural and compositional aspects of organizational networks contribute to diffusing peer-effects? Are some types of relationships and network partners more influential than others?
We rely on social comparison theory (Festinger, 1955) to propose and test historical and social explanations for peer effects in inter-organizational networks. Using longitudinal data on patient exchanges between hospitals in a regional community in Italy we reconstruct the personal network of each hospital, the set of relations of each hospital (ego) with collaborative network partners (alters), and the set of relations among alters. We also use information on a number of organizational and institutional characteristics to assess aggregate patterns of how individual and dyadic characteristics channel spillover effects among hospitals in the sample. Analytically, we follow the dyadic approach proposed by Rawlings and McFarland (2010) and test the presence of peer effects by measuring change in each hospital’s performance over time as related to change in alters’ performance.
Our results provide empirical evidence on how performance spillover effects that operate through networks ties propagate throughout organizational fields and communities.