scholarly journals Unpacking the “Black Box”: Understanding the Effect of Social Network Characteristics on Safety Behaviors of Construction Workers

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Shuquan Li ◽  
Pei Yang ◽  
Xiuyu Wu ◽  
Ge Wang ◽  
Meng Fan

How to improve the safety behaviors of construction workers has dogged the realm of construction project management. Previous studies mainly focused on the individual and/or organizational factors shaping safety behaviors, while there is a dearth of research focusing on the effect of individual-organizational nexus (i.e., the network embeddedness of individuals within the organization). Thus, this study employs social network analysis (SNA) and multivariable regression analyses to explore the relationship between the characteristics of social networks of construction workers (i.e., degree, closeness, and betweenness centralities) and their safety behaviors (i.e., safety participation and safety compliance), considering the mediating role of safety communication. The primary data were collected from ten Chinese construction projects. The results include the following three aspects. First, degree centrality, closeness centrality, and betweenness centrality all exert significant positive effects on safety participation. Closeness centrality yields a positive effect on safety compliance in formal networks. Degree centrality has a positive effect on both safety compliance and safety participation, whereas the other two centrality characteristics exhibit no significant effect in informal networks. Second, in formal networks, safety communication plays a partial mediation role between closeness centrality and safety compliance and a full mediation role between degree and closeness centralities and safety participation. Third, in informal networks, safety communication plays a full mediation role between degree centrality and safety compliance and a partial mediation role between degree centrality and safety participation. This study provides new insights for construction project management in achieving improved safety performance via shaping the social network characteristics.

2018 ◽  
Vol 8 (4) ◽  
pp. 291 ◽  
Author(s):  
Dongryeul Kim

  In order to find out the influence of Korean Middle School Students' relationship by science class applying STAD collaborative learning, this study conducted a social network analysis and sought to analyze the communication networks within the group and identified the change process of the type. The subject of this study was 30 students of the second grade at the girls' middle school located in Korea's Metropolitan City. For five weeks, science class applying STAD Collaborative Learning was implemented in the ‘reproduction and generation’ chapter. First, the class social network analysis showed that all the prices of density, degree centrality, closeness centrality, and betweenness centrality have risen after science class applying STAD Collaborative Learning. Also, the classroom's relationship index has improved. In other words, STAD Collaborative Learning encouraged interaction among students. Second, in order to research popularity, students' centrality analysis through the class social network analysis showed that top-ranked students' values of density, degree centrality, closeness centrality, and betweenness centrality appeared commonly high after science class applying STAD Collaborative Learning. Third, the analysis of the communication network change within six groups showed that all channel type appeared most often and circle type also appeared anew after science class applying STAD Collaborative Learning. In other words, it was possible to exchange information freely and communicate with all members of the group through STAD Collaborative Learning.


2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Jumartin Gerung

AbstrakPada kasus HIV dalam skala nasional, menunjukkan bahwa kelompok heteroseks juga termasuk sebagai kelompokutama yang paling berisiko menderita HIV/AIDS. Peningkatan ini mencolok terijadi sejak 2015 angkanya masih di 4.241 kasus, dan meningkat hingga lebih dari dua kali lipat pada 2016 yang mencapai 13.063 kasus. Data pemetaaninteraksi di sosial media khususnya wilayah Kendari terdapat sekitar 800 akun yang memberi interaksi perihal Gay.Hal ini diindikasikan akan mempengaruhi prevalensi kejadian HIV/AIDS di Kota Kendari. Penelitian ini bertujuan untukmemetakan interaksi perilaku berisiko Gay sebagai early warning system kasus HIV/AIDS. Social Network Analysismerupakan studi yang mempelajari tentang hubungan manusia dengan memanfaatkan teori graf. Penerapan SocialNetworkAnalysis dalam suatu aplikasi mampu menggambarkan relasi atau hubungan antar individu denganmelakukan visualisasi terkait centrality (titik pusat), between centrality (jalur pendek), juga closeness centrality yaknirata-rata jalur terpendek dari interaksi akun di laman FB. Untuk platform Facebook berdasarkan pada hasilpenghitungan diketahui bahwa akun yang berpengaruh terhadap interaksi jejaring sosial adalah akun Gay Kendariyang unggul pada nilai degree centrality,betweeness centrality, dan Closeness centrality. Akun Gay Kendari palingberpengaruh dalam interaksi jaringan sosial Facebook. Melalui social network analysis, penelitian ini memberikangambaran relasi perilaku berisiko LSL/Gay sebagai early warning system kasus HIV/AIDS di kota kendariKata kunci: analisis jaringan sosiai, gay, sistem peringatan dini, HIV/AIDS 


2020 ◽  
Vol 4 (5) ◽  
pp. 937-942
Author(s):  
Evangs Mailoa

Twitter is used to express about something that happened. In Indonesia since 2012, Twitter has been widely used for campaigns during regional or presidential elections. Apart from positive campaigns, negative campaigns and even black campaigns were carried out via Twitter, and tweets become twitwar. Twitter is a social network, so the data can be analyzed using a social network analysis approach. This research was conducted to analyze which nodes (actors) are influential using the degree, between, and closeness centrality methods, while the follower rank method is used for the analysis of popular actors in "# 4niesKingOfDrama". The data were 8895 nodes with 23257 edges taken from January 1 to February 20, 2020. The results showed that Degree Centrality was 212 with the actor who had the highest influence score was the account @ Bangsul__88 and actor @airin_nz was the actor with the highest popularity value with Follower Rank of 0.98211783. This study found that among the 10 main actors with the highest Degree Centrality values, there were several accounts that were buzzer accounts. The node (Actor) with the highest influence value is not necessarily the node with the highest popularity value.


2021 ◽  
Vol 5 (1) ◽  
pp. 98
Author(s):  
Gema Nusantara Bakry ◽  
Ika Merdekawati Kusmayadi

Peristiwa banjir bandang yang diakibatkan Siklon Seroja telah mengundang perhatian dan simpati masyarakat Indonesia. Berbagai upaya telah dilakukan untuk berkontribusi dalam upaya penanggulangan dampak yang diterima oleh masyarakat NTT. Salah satu upaya yang dilakukan oleh masyarakat adalah mengampanyekan gerakan sosial digital #SolidaritasUntukNTT di Twitter. Gerakan sosial digital melalui pesan-pesan tertentu dapat menggugah kesadaran bagi penggunanya. Untuk mengetahui efektivitas penyebaran pesan dalam gerakan sosial digital dapat divisualisasikan menggunakan metode Social Network Analysis (SNA).  Penelitian ini bertujuan untuk memvisualisasikan peran pers dalam mendistribusikan pesan gerakan sosial digital dengan tagar #SolidaritasUntukNTT. Metode penelitian yang digunakan adalah analisis jaringan sosial dengan teori graf di Twitter. Hasil analisis dan visualisasi jaringan dilakukan di aplikasi Gephi dengan algoritma Yifan Hu untuk melihat distribusi pola pesan dan peran pers pada tagar #SolidaritasUntukNTT. Penelitian ini menggambarkan tipe jaringan two mode yang terdiri dari interaksi antara individu dan organisasi dengan pola komunikasi radial personal network yang memiliki ciri jaringan terbuka dan kohesivitas yang rendah dengan arah relasi directed dan asimetris. Analisis peran pers diukur melalui sentralitas aktor untuk mengetahui degree centrality, closeness centrality, betweenness centrality dan eigenvector centrality. Aktor @vice_id diketahui sebagai aktor yang memiliki degree dan eigenvector centrality tertinggi dibandingkan dengan aktor pers lainnya. Aktor @idntimes dan @detikcom memiliki nilai closeness dan betweenness centrality yang lebih tinggi dari media lainnya. Analisis jaringan sosial memberikan pemahaman terkait distribusi pesan dalam media sosial untuk mengetahui efektivitas pesan yang didistribusikan oleh beberapa aktor jaringan, khususnya peran pers dalam mengampanyekan gerakan sosial di media. Oleh karena itu, metode SNA dapat digunakan untuk penelitian jurnalisme data. 


2017 ◽  
Vol 14 (3) ◽  
pp. 201 ◽  
Author(s):  
Rio Oktora ◽  
Andry Alamsyah

Selama beberapa tahun terakhir, internet telah berkembang dengan cepat seiring dengan perkembangan teknologi. Data percakapan yang terdapat di media sosial dapat dimanfaatkan untuk melihat pola interaksi dan aktor yang paling berperan pada event JGTC 2013 melalui media sosial Twitter. Penelitian ini memanfaatkan big data dari media sosial Twitter yang diperoleh dari Twitter melalui API (Aplication Programming Interface) dengan bantuan teknis dari NoLimitID (perusahaan social media monitoring & analytic tools). Data tersebut kemudian diolah dengan pendekatan Social Network Analysis. Software yang digunakan untuk menghitung dan menvisualisasikan hasil analysis adalah Gephi. Penentuan aktor yang berperan dalam event JGTC 2013 dihitung berdasarkan centrality yang terdiri dari degree centrality, betweenness centrality, closeness centrality, dan eigenvector centrality. Sampel dalam penelitian ini adalah tweet yang berupa interaksi (terdapat mention, baik berupa reply maupun qoute retweet) yang memuat kata 'JGTC' dan '#JGTC36' pada 1 Desember 2013. Hasil penelitian pada event JGTC 2013 terdapat 7624 node (akun) yang terlibat dengan 7445 edge (interaksi) yang terjadi di network tersebut. Aktor (node) yang paling berpengaruh dalam network JGTC secara keseluruhan adalah raisa6690 yang merupakan bintang tamu pengisi acara event JGTC 2013


Literator ◽  
2013 ◽  
Vol 34 (2) ◽  
Author(s):  
Burgert A. Senekal

Etienne van Heerden’s Toorberg can be approached as a modern, postcolonial farm novel, partly because it challenges the concept of lineage of inheritance, which is characteristic of the traditional farm novel. Lineage of inheritance implies a strong family bond, and it is therefore instructive to investigate how family ties function within this novel. The article views family ties within Toorberg using Social Network Analysis (SNA), a largely unknown theoretical framework that can also be applied within the study of literature. It is shown how characters’ positions in this network can be calculated in terms of degree centrality, closeness centrality, Eigenvector centrality and betweenness centrality, and how these measures expose the way in which this novel undermines the traditional concept of inheritance.


2020 ◽  
Vol 17 (1) ◽  
pp. 88-95
Author(s):  
Ni Made Distiara Landephy Aryashila ◽  
Silvyana Nur Haliza ◽  
Naufal Farras Maulana ◽  
Doni Achmad Heniawan ◽  
Yudianto Yudianto

Football is a popular sport that is loved by a lot of society in the world, ranging from children to adult is very enthusiastic when discussing about soccer. The process of buying and transferring players is one element that can’t be separated in football, this process is done to improve performance and replace players who move to other clubs. Spanish league or known as La Liga is one of the major league that often transfers player, information regarding player transfers and the club itself can be seen in each season on the website transfermarkt.com. In this study we chose the Spanish League as an object of research, we use the Social Network Analysis Basic Concept technique to determine the key players of each club and players in the Spanish League in the 2015-2020 period by analyzing degree centrality, closeness centrality, dan betweenness centrality. the results of this study were displayed  Sevilla FC as a club key player, and Juanfran as a key player player


2014 ◽  
Vol 3 (1) ◽  
pp. 49-64 ◽  
Author(s):  
Todd D. Smith ◽  
David M. DeJoy

Purpose – The purpose of this paper is to test an initial model of safety climate for firefighting. Relationships between safety climate, safety behaviors and firefighter injuries were examined. Design/methodology/approach – Data were collected from 398 professional firefighters in the southeastern USA. Structural equation modeling, using a zero-inflated Poisson regression method, was used to complete the analyses. Findings – Safety climate, as a higher order factor, was comprised of four factors including management commitment to safety, supervisor support for safety, safety programs/policies and safety communication. Both safety compliance behaviors and safety participation behaviors were significantly, positively associated with safety climate. Both behaviors were deemed protective and were associated with reductions in injury. Safety climate relations to injury were interesting, but somewhat ambiguous. Safety climate significantly predicted membership in the “always zero” injury group. For those not in the “always zero” group, the relationship between safety climate and injury was positive, which was not completely surprising as direct relationships between safety climate and injury have been insignificant and opposite to predictions in studies using retrospective data and may be attributed to reverse causation. Originality/value – This novel study illustrates the importance of both organizational and work unit factors in helping shape safety climate perceptions among firefighters. The results also support the safety climate – behavior – injury model and show that a positive safety climate encourages safer behaviors among firefighters. Lastly, the findings confirm that both safety compliance behaviors and safety participation behaviors are important to reducing individual firefighter injury experience.


2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Supot Noopataya ◽  
Sukanya Thongratsakul ◽  
Chaithep Poolkhet

The aim of this study is to analyse the pattern of cattle movement in Sukhothai province, Thailand. A validated questionnaire was applied to 308 respondents related to cattle farming using one-step snowball sampling. The results showed that most of the nodes are farmers who move their animals in the province. The average normalized degree centrality and normalized closeness centrality were low (<0.01 and 0.04, resp.). We found that traders are the nodes with a high value of centrality. This corresponds with the cutpoint analysis results that traders are outstanding. In conclusion, the relevant authorities should focus on the nodes such as traders for controlling disease. However, a measure to detect disease in the early stages needs to be implemented.


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