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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

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Published on: May 31, 2019

Enhancing decision-making support by mining social media data with social network analysis.

Manuela Freire^1,2, Francisco Antunes^3,2, João Paulo Costa¹

¹Av Dias da Silva 165, 3004-512 Coimbra, Portugal Faculty of Economics, CeBER, Univ Coimbra.

Social Network Analysis and Mining

|May 22, 2023

Summary

Social network analysis (SNA) on airline social media helps identify key customers and improve service. This data-driven approach enhances customer satisfaction and operational efficiency, especially during disruptions.

Keywords:

Data mining Decision Discourse Network analysis SNA Social network analysis

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Area of Science:

Airline industry
Social media analytics
Customer relationship management

Background:

Airlines face challenges in managing customer service during disruptions like strikes.
Online social networks (OSNs) offer a rich source of customer interaction data.
Effective analysis of OSN data can provide valuable insights for decision support.

Observation:

Social network analysis (SNA) was applied to an airline's Facebook data.
Interactions and discursive exchanges between users were analyzed.
Key metrics were calculated to identify influential users and service issues.

Findings:

SNA metrics effectively detect influential customers (satisfied or dissatisfied).
Analysis enables addressing pending requests and enhancing customer satisfaction.
Metrics reveal opportunities to improve call-center performance and responsiveness.

Implications:

Provides a theoretical framework integrating social interaction and SNA for airline decision support.
Offers practical insights for companies to leverage SNA for improved customer service.
Highlights the importance of social media monitoring for strategic decision-making.