Semantic network edges: a human-machine approach to represent typed relations in social networks

2015 ◽  
Vol 19 (1) ◽  
pp. 71-81 ◽  
Author(s):  
M. Cristina Pattuelli ◽  
Matthew Miller
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Semantic Network ◽  
Contextual Information ◽  
Open Data ◽  
Entity Recognition ◽  
Semantic Web Technologies ◽  
Data Set ◽  
Content Type ◽  
External Data

Purpose – The purpose of this paper is to describe a novel approach to the development and semantic enhancement of a social network to support the analysis and interpretation of digital oral history data from jazz archives and special collections. Design/methodology/approach – A multi-method approach was applied including automated named entity recognition and extraction to create a social network, and crowdsourcing techniques to semantically enhance the data through the classification of relations and the integration of contextual information. Linked open data standards provided the knowledge representation technique for the data set underlying the network. Findings – The study described here identifies the challenges and opportunities of a combination of a machine and a human-driven approach to the development of social networks from textual documents. The creation, visualization and enrichment of a social network are presented within a real-world scenario. The data set from which the network is based is accessible via an application programming interface and, thus, shareable with the knowledge management community for reuse and mash-ups. Originality/value – This paper presents original methods to address the issue of detecting and representing semantic relationships from text. Another element of novelty is in that it applies semantic web technologies to the construction and enhancement of the network and underlying data set, making the data readable across platforms and linkable with external data sets. This approach has the potential to make social networks dynamic and open to integration with external data sources.

The impact of organizational social networks on salespeople’s negative headquarters stereotypes

2020 ◽  
Vol 35 (12) ◽  
pp. 1901-1913
Author(s):  
Babak Hayati ◽  
Sandeep Puri
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sales Performance ◽  
Sales Managers ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
Network Patterns ◽  
The Impact ◽  
Sales Forces

Purpose Extant sales management literature shows that holding negative headquarters stereotypes (NHS) by salespeople is harmful to their sales performance. However, there is a lack of research on how managers can leverage organizational structures to minimize NHS in sales forces. This study aims to know how social network patterns influence the flow of NHS among salespeople and sales managers in a large B2B sales organization. Design/methodology/approach The authors hypothesize and test whether patterns of social networks among salespeople and sales managers determine the stereotypical attitudes of salespeople toward corporate directors and, eventually, impact their sales performance. The authors analyzed a multi-level data set from the B2B sales forces of a large US-based media company. Findings The authors found that organizational social network properties including the sales manager’s team centrality, sales team’s network density and sales team’s external connectivity moderate the flow of NHS from sales managers and peer salespeople to a focal salesperson. Research limitations/implications First, the data was cross-sectional and did not allow the authors to examine the dynamics of social network patterns and their impact on NHS. Second, The authors only focused on advice-seeking social networks and did not examine other types of social networks such as friendship and trust networks. Third, the context was limited to one company in the media industry. Practical implications The authors provide recommendations to sales managers on how to leverage and influence social networks to minimize the development and flow of NHS in sales forces. Originality/value The findings advance existing knowledge on how NHS gets shared and transferred in sales organizations. Moreover, this study provides crucial managerial insights with regard to controlling and managing NHS in sales forces.

Friend recommendation for healthy weight in social networks

2015 ◽  
Vol 115 (7) ◽  
pp. 1251-1268 ◽  
Author(s):  
Anming Li ◽  
Eric W.T. Ngai ◽  
Junyi Chai
Keyword(s):  
Social Networks ◽  
Weight Loss ◽  
Social Network ◽  
Healthy Lifestyle ◽  
Overweight And Obesity ◽  
Healthy Weight ◽  
Data Set ◽  
Content Type ◽  
Friend Recommendation ◽  
Target User

Purpose – The purpose of this paper is to propose a new approach recommending friends to social networking users who are also using weight loss app in the context of social networks. Design/methodology/approach – Social network has been recognized as an effective way to enhance overweight and obesity interventions in past studies. However, effective measures integrating social network with weight loss are very limited in the healthcare area. To bridge this gap, this study develops a measure for friend recommendation using the data obtained by weight loss apps; designs methods to model weight-gain-related behaviors (WGRB); constructs a novel “behavior network;” and develops two measurements in experiments to examine the proposed approach. Findings – The approach for friend recommendation is based on Friend Recommendation for Health Weight (FRHW) algorithm. By running this algorithm on a real data set, the experiment results show that the algorithm can recommend a friend who has a healthy lifestyle to a target user. The advantages of the proposed mechanism have been well justified via comparisons with popular friend recommenders in past studies. Originality/value – The conventional methods for friend recommenders in social networks are only concerned with similarities of pairs rather than interactions between people. The system cannot account for the potential influences among people. The method pioneers to model a WGRB as recommendation mechanism that allow recommended friends to simultaneously fulfill two criteria. They are: first, similarity to the target person; and second, ensuring the positive influence toward weight loss. The second criterion is obviously important in practice and thus the approach is valuable to the literature.

Personality, risk tolerance and social network use: an exploratory study

2016 ◽  
Vol 42 (6) ◽  
pp. 536-552 ◽  
Author(s):  
Shaista Wasiuzzaman ◽  
Siavash Edalat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Financial Risk ◽  
Ordinary Least Squares ◽  
Risk Tolerance ◽  
Network Activity ◽  
Least Squares Regression ◽  
Content Type ◽  
Financial Risk Tolerance

Purpose – The vast amount of information available via online social networks (OSN) makes it a very good avenue for understanding human behavior. One of the human characteristics of interest to financial practitioners is an individual’s financial risk tolerance. The purpose of this paper is to look at the relationship between an individual’s OSN behavior and his/her financial risk tolerance. Design/methodology/approach – The study uses data collected from a sample of 220 university students and the backward variables selection ordinary least squares regression analysis technique to achieve its objective. Findings – The results of the study find that the frequency of logging on to social network sites indicates an individual who has higher financial risk tolerance. Additionally, the increasing use of social networks for social connection is found to be associated with lower financial risk tolerance. The results are mostly consistent when the sample is split based on prior financial knowledge. Originality/value – To the authors’ knowledge this is the first study which documents the possibility of understanding an individual’s financial risk tolerance via his/her social network activity. This provides investment/financial consultants with more avenues for gathering information in order to understand their current or potential clients hence providing better services.

Computational modeling of Weibo user influence based on information interactive network

2016 ◽  
Vol 40 (7) ◽  
pp. 867-881 ◽  
Author(s):  
Dingguo Yu ◽  
Nan Chen ◽  
Xu Ran
Keyword(s):  
Social Networks ◽  
Computational Model ◽  
Large Scale ◽  
Mobile Internet ◽  
Activity Level ◽  
Message Content ◽  
Data Set ◽  
Sina Weibo ◽  
Content Type ◽  
User Influence

Purpose With the development and application of mobile internet access, social media represented by Weibo, WeChat, etc. has become the main channel for information release and sharing. High-impact users in social networks are key factors stimulating the large-scale propagation of information within social networks. User influence is usually related to the user’s attention rate, activity level, and message content. The paper aims to discuss these issues. Design/methodology/approach In this paper, the authors focused on Sina Weibo users, centered on users’ behavior and interactive information, and formulated a weighted interactive information network model, then present a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc., the model incorporated the time dimension, through the calculation of users’ attribute influence and interactive influence, to comprehensively measure the user influence of Sina Weibo users. Findings Compared with other models, the model reflected the dynamics and timeliness of the user influence in a more accurate way. Extensive experiments are conducted on the real-world data set, and the results validate the performance of the approach, and demonstrate the effectiveness of the dynamics and timeliness. Due to the similarity in platform architecture and user behavior between Sina Weibo and Twitter, the calculation model is also applicable to Twitter. Originality/value This paper presents a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc.

scholarly journals A new database structure for the IHFC Global Heat Flow Database

2021 ◽  
Vol 4 (1) ◽  
pp. 1-14
Author(s):  
Sven Fuchs ◽  
Graeme Beardsmore ◽  
Paolo Chiozzi ◽  
Orlando Miguel Espinoza-Ojeda ◽  
Gianluca Gola ◽  
...  
Keyword(s):  
Heat Flow ◽  
International Association ◽  
Open Data ◽  
Flow Data ◽  
Ocean Drilling Program ◽  
Data Set ◽  
Data Services ◽  
External Data ◽  
Database Structure ◽  
Starting Point

Periodic revisions of the Global Heat Flow Database (GHFD) take place under the auspices of the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI). A growing number of heat-flow values, advances in scientific methods, digitization, and improvements in database technologies all warrant a revision of the structure of the GHFD that was last amended in 1976. We present a new structure for the GHFD, which will provide a basis for a reassessment and revision of the existing global heat-flow data set. The database fields within the new structure are described in detail to ensure a common understanding of the respective database entries. The new structure of the database takes advantage of today's possibilities for data management. It supports FAIR and open data principles, including interoperability with external data services, and links to DOI and IGSN numbers and other data resources (e.g., world geological map, world stratigraphic system, and International Ocean Drilling Program data). Aligned with this publication, a restructured version of the existing database is published, which provides a starting point for the upcoming collaborative process of data screening, quality control and revision. In parallel, the IHFC will work on criteria for a new quality scheme that will allow future users of the database to evaluate the quality of the collated heat-flow data based on specific criteria.

The role of online social networks in university students’ environmentally responsible behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amirreza Rezaei ◽  
Saba Ahmadi ◽  
Hamid Karimi
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Environmental Attitudes ◽  
Environmental Issues ◽  
Control Group ◽  
Environmentally Responsible Behavior ◽  
Content Type ◽  
Responsible Behavior ◽  
Environmentally Responsible

Purpose This study aims to determine the effect of online social networks on university students’ environmentally responsible behavior (ERB). This research aimed to develop and test a behavioral model in the context of online social networks, where students’ attitudes, knowledge and behavior influence their ERB. Design/methodology/approach This study used a quasi-experiment with a pretest-posttest design and a random parallelization control group. The research used a questionnaire to assess ERB, environmental attitudes and environmental knowledge. The researcher randomly assigned 120 students to an experimental and a control group of equal size. Both groups initially completed a pretest. The experimental group was trained in environmental issues over four months (an academic semester) via an online social network. Findings The findings indicated that the social network had a significant effect on motivating ERB. Additionally, it improved environmental attitudes. According to the results, online social networks such as Facebook can significantly aid in teaching and learning environmental issues in formal academic settings. Originality/value Online social networks facilitated significant cognitive progress in environmental education. The primary objective is to educate students about ERB.

Academic social networks and collaboration patterns

2019 ◽  
Vol 38 (2) ◽  
pp. 293-307
Author(s):  
Po-Yen Chen
Keyword(s):  
Social Networks ◽  
Data Collection ◽  
Research Collaboration ◽  
Open Data ◽  
Data Sets ◽  
Content Type ◽  
Open Government Data ◽  
Collaboration Patterns ◽  
Academic Social Networks ◽  
Government Data

Purpose This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration. Design/methodology/approach This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns. Findings Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared. Originality/value In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.

Who is the boss? Identifying key roles in telecom fraud network via centrality-guided deep random walk

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Chun Chang ◽  
Kuan-Ting Lai ◽  
Seng-Cho T. Chou ◽  
Wei-Chuan Chiang ◽  
Yuan-Chen Lin
Keyword(s):  
Social Network ◽  
Random Walk ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Random Walks ◽  
Interpersonal Relationships ◽  
Interaction Network ◽  
Data Set ◽  
Content Type ◽  
Structural Equivalence

PurposeTelecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.Design/methodology/approachThe authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.FindingsThe authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.Research limitations/implicationsThe study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.Originality/valueThis paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.

Patterns of frequent user interactions in blogosphere

2020 ◽  
Author(s):  
Krzysztof Rudek ◽  
Jarosław Koźlak
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Relative Difference ◽  
Pattern Identification ◽  
Frequent Patterns ◽  
Frequent User ◽  
User Interactions ◽  
Data Set ◽  
Political Issues

Abstract The aim of the paper is to identify and categorize frequent patterns describing interactions between users in social networks. We analyze a social network with relationships between users that evolve in time already identified. In our research, we discover patterns based on frequent interactions between groups of users. The patterns are described by the characteristics of these interactions, such as their reciprocity, or the relative difference between estimations of global influences of the users participating in the discussions. The modification of the apriori algorithms is applied as one of the methods for pattern identification. The analyzed social network is built using the data set containing data from the Polish blog website salon24, which concerns mostly socio-political issues.

scholarly journals Social networks, corruption and institutions of accounting, auditing and accountability

2019 ◽  
Vol 32 (2) ◽  
pp. 508-530 ◽  
Author(s):  
Joseph Phiri ◽  
Pinar Guven-Uslu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Economic Status ◽  
Wealth Distribution ◽  
Network Activity ◽  
Structured Interviews ◽  
Government Officials ◽  
Content Type ◽  
Research Findings ◽  
African Context

Purpose The purpose of this paper is to investigate institutions of accountability in Zambia in order to understand how social networks may influence such institutions not to discharge their mandates as expected from time to time. The study equally seeks to explore how social networks may perpetuate corrupt activities and compromise the functioning of institutions of accountability. Design/methodology/approach The conceptual framework adopted in this study draws on insights from social network theory (SNT) and Bourdieu’s ideas of capital to devise a critical lens for investigating network activity and its influence on the functioning of institutions of accountability. Qualitative data were collected through semi-structured interviews with respondents drawn from different institutions of accountability. Social network analysis was conducted through content analysis. Findings Research findings highlight the presence of networks of a corrupt nature operating within government structures and some institutions of accountability. Manifested in the form of systemic and familial archetypes, these networks appear to be championed and propelled by senior government officials like controlling officers and other actors of a political nature including ministers and presidents. Most of these corrupt activities are organised through brokerage mechanisms that interface internal and external networks. Research limitations/implications Due to the clandestine nature of corruption activities, however, the study was unable to determine measures of centrality and density since these details were not forthcoming during interviews. Such information could only become available if willing individuals involved in corruption could be identified so that they explain who they conduct their corruption with together with the number of connections involved and the most influential individuals in those networks. Social implications This study helps us to understand that activities of a corrupt nature are often undertaken through well-connected groups and networks that make it difficult for institutions of accountability to detect and untangle such activity. The study also suggests that accountants and other accountability actors may have forgotten that accounting is not just a technical discourse for enhancing one’s economic status but is an ethical profession as well. There is a great need to put institutions in place which should hold everyone, including the president and ministers, accountable to the Zambian people in the light of wrongdoing. Dismantling the corrupt network activities inferred from the data entails a complete top-down change in systems of politics, governance, wealth distribution and social values. Originality/value This study contributes towards filling the gap of undertaking accounting research of a critical nature focussed on African contexts (Rahaman, 2010). The paper is equally an attempt at providing empirical flesh to Laughlin’s (1991) framework on organisational transformations through complementing that framework with SNT. The study is also among the first to draw on the experiences and insights of actors working within institutions of accountability to highlight accountability challenges within an African context.

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