Getting decision support from context-specific online social networks: a case study

Abstract

The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN's contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN's data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers' requests, solely based on their Facebook posts, showing that the unstructured data of the web's discourse can be used to support this kind of decision processes.

Applying Social Network Analysis and Data Mining Techniques to Support Decision-Making: A Case Study

“…Semantic processing transformed unstructured data, from the obtained 769 posts, into a standardized form. We then used the cleaning database and the algorithm proposed in Freire, Antunes [1] to perform the semantic analysis.…”

“…Businesses can use tools to monitor online social networks (OSN), to filter social conversations (web discourse) based on certain keywords [1], such as company name, services, etc. The collected information can be integrated into internal systems using data visualization to improve the view of customer interactions.…”

“…SNA in particular includes various important centrality metrics associated with social networks' studies (for more details please see Freire, Antunes [1], Wasserman and Faust [3], Moreira, Carvalho [4], Savic, Ivanovic [5]). NLP is a computer science field that uses machines to get knowledge from text written in natural language [6,7] and DM refers to the automated detection of interesting data structures, including techniques that aim to infer, from data, models that attain specific purposes [2,8].…”

“…According to Bartos and Badanik [9] and SimpliFlying [10], in spite of the fact that OSN has become an important part of airline operations, for building relationships with passengers and to stay in touch with them, OSN data analysis isn't receiving the same attention in supporting decisionmaking or for aiding in crisis management. In this paper we stand that the application of SNA techniques can allow a deeper understanding of airlines' OSN, thus helping to get useful information for previous mentioned purposes [1].…”

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

“…OSNs can be monitored to filter social conversations (Freire et al 2022 ), providing businesses tools to better understand their customers and to build customer profiles. Moreover, by combining different techniques it is possible to interpret social networks’ activity.…”