Open AccessExponential Random Graph Models (ERGMs) to analyze the online shop networking in Instagram
Author(s) -
Rokhana Dwi Bekti,
Noviana Pratiwi,
Y. Niami,
Edhy Sutanta,
Erna Kumalasari Nurnawati
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1456/1/012025
Subject(s) - exponential random graph models , random graph , computer science , social media , social network (sociolinguistics) , graph , network analysis , network science , advertising , theoretical computer science , complex network , world wide web , business , engineering , electrical engineering
Social media is one of the important media for entrepreneurs in marketing their products, one of the popular is Instagram. Account activity on Instagram greatly influences marketing and sales levels, such as network, number of follower, following or posting. This study applies the Exponential Random Graph Models (ERGMs) to analyze how the network structure, follower, following, and total posts were affect to the online shop network accounts on Instagram. The data analyzed were 28 samples Instagram accounts which domiciled in DIY and Central Java Province. The predictor variables are non-directed network structure (edges, 2-star) and individual activeness (number of followers, number of following, and total post). The network structure graph constructed a directed network with 41 nodes and 104 edges. Based on ERGMs and significance test with α=5%, the network structure and characteristic of account have a significant influence on the networks between the online shop. The parameter estimation results can be interpreted as follows, an online shop does not take the initiative to make friends or network with another account, because focused on making network with the consumers. If there are more followers, then there is a high probability to get a connection between accounts. This result can be used as a marketing strategy through social media.