scholarly journals A Novel Approach to the Measurement of Bourdieusian Social Capital within Institutional Pages and Profiles

2022 ◽  
Vol 29 (1) ◽  
pp. 11-27
Author(s):  
Alan Keller Gomes ◽  
Kaique Matheus Rodrigues Cunha ◽  
Guilherme Augusto da Silva Ferreira

We present in this paper a novel approach for measuring Bourdieusian Social Capital (BSC) within  Institutional Pages and Profiles. We analyse Facebook's Institutional Pages and Twitter's Institutional Profiles. Supported by Pierre Bourdie's theory, we search for directions to identify and capture data related to sociability practices, i. e. actions performed such as Like, Comment and Share. The system of symbolic exchanges and mutual recognition treated by Pierre Bourdieu is represented and extracted automatically from these data in the form of generalized sequential patterns. In this format, the social interactions captured from each page are represented as sequences of actions. Next, we also use such data to measure the frequency of occurrence of each sequence. From such frequencies, we compute the effective mobilization capacity. Finally, the volume of BSC is computed based on the capacity of effective mobilization, the number of social interactions captured and the number of followers on each page. The results are aligned with Bourdieu's theory. The approach can be generalized to institutional pages or profiles in Online Social Networks.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.


2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Clio Andris ◽  
Dipto Sarkar

<p><strong>Abstract.</strong> Interpersonal relationships are an important part of social and personal health. Studies of social capital show that individuals and communities with stronger ties are have an economic and health advantage. Yet, loneliness and isolation are becoming major public health issues. There is a pressing need to measure where relationships are strong and how accessible one’s social ties are, in order to learn how to better support face-to-face meetings and promote social health in society. However, the datasets we use to study people and human behaviour are most often mobility data and census data &amp;ndash; which tell us little about personal relationships. These data can be augmented with information about where people have ties, and how their relationships unfold over geographic space. The data we use to study the built environment include building footprints and infrastructure, and we can annotate these data by how (well) infrastructure supports different kinds of relationships, in order to ask new questions about how the landscape encourages relationships.</p><p> We suggest a list of methods for representing interpersonal relationships and social life at various socio-spatial levels of aggregation. We give an example of each, with an effort to span various use cases and spatial scales of data modelling.</p><p> <strong>Dyads (line) and Ego-based (star):</strong> This geometric model represents a relationship between two individuals (Figure 1A). The individuals can be geolocated to households, administrative units, real-time locations, etc. The tie can be given a nominal category such as family or co-worker, and edge weights that signify reported relationship strength, frequency of contact, frequency of face-to-face meeting, et cetera. Star models represent a central individual and his/her geolocated ties (that radiate from the centre). The star illustrates the theoretical concept of personal extensibility.</p><p> <strong>Points of Interest (points):</strong> Points of interest provide a place-based perspective (note that these entities can also be represented as polygons such as building footprints, or lines such as gradients of interaction on a subway). Certain places are better suited for fostering relationships than others (Figure 1B), and each can be annotated with their ability to foster: new ties (a nightclub), gender-bonding ties (bowling leagues), romantic ties (romantic restaurants), inter-generational ties (a religious facility), professional ties (conferences), et cetera.</p><p> <strong>Polygons/Administrative Units (polygons):</strong> These data are attached to administrative areal units (Census boundaries, provinces, zones, etc.). The data represent surveyed data on relationship-related variables in censuses, social surveys and social capital surveys. These surveys ask about trust, friendliness with neighbours, social life, belongingness to institutions, and more (Figure 1C), illustrating the social health of an area.</p><p> <strong>Aggregate Flows and Social Networks (lies and networks):</strong> This model illustrates the geolocated, social ties within a spatial extent, i.e. the social networks of a group of many people over a large extent (Figure 1D). Data can be sourced from social media, telecommunications patterns, and other declarations of relationships.</p><p> <strong>Regions (polygons):</strong> Regions, that may describe neighbourhoods within one city, or an agglomeration of cities, can be defined by social ties. Instead of commuting or economic ties, regions are defined by a preponderance of social ties within a given polygon, and a lack of ties between polygons (or between the polygon and any external area). Social regions represent a likeness and strong ties between the people that live within the region (Figure 1E).</p><p> Given these methods for representing social life and interpersonal relationships as GIS data, new questions may arise. At the <strong>dyadic level</strong>: how can we map the presence of a relationship between two people? At the <strong>ego-based level</strong>: how far and with what kind of diversity do people have ties? At the <strong>point of interest level</strong>: what kinds of mapable data can describe places’ ability to create new relationships and foster existing relationships? At the <strong>polygonal level</strong>: what kinds of mapable data can show where relationships are strong or weak? At the <strong>levels of flows and networks</strong>: what kinds of mapable data can describe systems of diffusion? At the <strong>regional level</strong>: what physical and administrative boundaries guide social ties?</p><p> For cartographers and geographic modellers looking to study social life, data acquisition, analysis, and mapping are challenges. The point of this extended abstract is to inventory the possibilities of mapping these data, open a dialog for experimenting with what kinds of symbologies, associated variables, classification schemes, visualization techniques and data collection opportunities are available for this purpose. We also hope to create spaces for comparative studies that describe the implications of these choices. In our search, we find that the major research challenges are the following: 1) privacy 2) geolocatable data 3) qualitative vs. quantitative data and 4) assurance statistically-significant samples sizes 5) analysis and modelling 6) visualization. Nevertheless, our goal is to make these indicators and data more GIS-friendly and available to geospatial analysts, modellers and cartographers.</p>


2019 ◽  
Author(s):  
Arlika Anindya Putri

Purpose – The purpose of this study is to develop a structural equation model to explain the complexrelationship between social network and firm performance by introducing the mediating role of trust, sellingcapability and pricing capability.Design/methodology/approach – The research model with hypothesis development was derived basedon the literature. To provide empirical evidence, this study carried out a survey in which the data wereequated with a list of questionnaires with a random survey of 380 small and medium enterprises (SMEs) inthe Indonesian context.Findings – This study indicates that the use of social media in management process will not affect theincreasing firm performance, unless the firms build trust upon social networks. The social network with trustallows the firms to gain a pricing capability and a selling capability, which brings a positive impact on firmperformance. The results also show that the selling and the pricing capabilities become essential following theutilizing the social media, which concerns on trust building.Research limitations/implications – This study focused on the small-to-medium context, which hasconventionally provided an exemplary site for the development of social capital theory but raises issues ofgeneralizability across different contexts.Practical implications – To the managers, it is advisable to encourage their employees to consciouslyexploit the selling capability by enhancing the business networks via social media to achieve the firmperformance.Originality/value – This paper contributes to the social capital theory by explaining the mediating role oftrust in the complex relationship between social network and firm performance. This study provides evidencethat trust plays a pivotal role in social networks, which enable the observed firms to achieve the performance.


2018 ◽  
pp. 978-1003
Author(s):  
Asmae El Kassiri ◽  
Fatima-Zahra Belouadha

The Online Social Networks (OSN) have a positive evolution due to the diversity of social media and the increase in the number of users. The revenue of the social media organizations is generated from the analysis of users' profiles and behaviors, knowing that surfers maintain several accounts on different OSNs. To satisfy its users, the social media organizations have initiated projects for ensuring interoperability to allow for users creating other accounts on other OSN using an initial account, and sharing content from one media to others. Believing that the future generations of Internet will be based on the semantic web technologies, multiple academic and industrial projects have emerged with the objective of modeling semantically the OSNs to ensure interoperability or data aggregation and analysis. In this chapter, we present related works and argue the necessity of a unified semantic model (USM) for OSNs; we introduce a kernel of a USM using standard social ontologies to support the principal social media and it can be extended to support other future social media.


Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo

Social web sites are used daily by many millions of users. They have attracted users with very weak interest in technology, including absolute neophytes of computers in general. Common users of social web sites often have a carefree attitude in sharing information. Moreover, some system operators offer sub-par security measures, which are not adequate for the high value of the published information. For all these reasons, online social networks suffer more and more attacks by sophisticated crackers and scammers. To make things worse, the information gathered from social web sites can trigger attacks to even more sensible targets. This work reviews some typical social attacks that are conducted on social networking systems, describing real-world examples of such violations and analyzing in particular the weakness of password mechanisms. It then presents some solutions that could improve the overall security of the systems.


Author(s):  
Dmitry Zinoviev

The issue of information diffusion in small-world social networks was first systematically brought to light by Mark Granovetter in his seminal paper “The Strength of Weak Ties” in 1973 and has been an area of active academic studies in the past three decades. This chapter discusses information proliferation mechanisms in massive online social networks (MOSN). In particular, the following aspects of information diffusion processes are addressed: the role and the strategic position of influential spreaders of information; the pathways in the social networks that serve as conduits for communication and information flow; mathematical models describing proliferation processes; short-term and long-term dynamics of information diffusion, and secrecy of information diffusion.


Author(s):  
Crystal R. Chambers

Rural students are more likely to complete their high school diploma but less likely than urban or suburban students to enroll in college. This is in part due to exposure to college and social capital, particularly differential access to social networks including individuals with college degrees. Schools can play a role in bridging the social capital gap as school teachers and counselors are individuals with college degrees who live in and near rural communities. In this vein, teachers and counselors can inspire the college aspirations of rural students, a prerequisite for student engagement in college choice processes.


2013 ◽  
Vol 5 (4) ◽  
pp. 34-54 ◽  
Author(s):  
Panagiotis Andriotis ◽  
Zacharias Tzermias ◽  
Anthi Mparmpaki ◽  
Sotiris Ioannidis ◽  
George Oikonomou

While technology matures and becomes more productive, mobile devices can be affordable and, consequently, fully integrated in people's lives. After their unexpected bloom and acceptance, Online Social Networks are now sources of valuable information. The authors therefore use them for tasks varying from direct marketing to forensic analysis. The authors have already seen Social Network Forensics techniques focused on particular networks implementing methods that collect data from user accounts. During the forensic analysis it is common to aggregate information from different sources but, usually, this procedure causes correlation problems. Here, the authors present their method to correlate data gathered from various social networks in combination with smartphones creating a new form of social map of the user under investigation. In addition, the authors introduce a multi level graph that utilises the correlated information from the smartphone and the social networks and demonstrates in three dimensions the relevance of each contact with the suspect.


Author(s):  
Jaymeen R. Shah ◽  
Hsun-Ming Lee

During the next decade, enrollment growth in Information Systems (IS) related majors is unlikely to meet the predicted demand for qualified IS graduates. Gender imbalance in the IS related program makes the situation worse as enrollment and retention of women in the IS major has been proportionately low compared to male. In recent years, majority of high school and college students have integrated social networking sites in their daily life and habitually use these sites. Providing female students access to role models via an online social network may enhance their motivation to continue as an IS major and pursue a career in IS field. For this study, the authors follow the action research process – exploration of information systems development. In particular, a Facebook application was developed to build the social network connecting role models and students. Using the application, a basic framework is tested based on the gender of participants. The results suggest that it is necessary to have adequate number of role models accessible to students as female role-models tend to select fewer students to develop relationships with a preference for female students. Female students likely prefer composite role models from a variety of sources. This pilot study yields valuable lessons to provide informal learning fostered by role modeling via online social networks. The Facebook application may be further expanded to enhance female students' interests in IS related careers.


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