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Social media as a main source of customer feedback: alternative to customer satisfaction surveys

Published: 15 January 2020 Publication History

Abstract

Customer satisfaction surveys, which have been the most common way of gauging customer feedback, involve high costs, require customer active participation, and typically involve low response rates. The tremendous growth of social media platforms such as Twitter provides businesses an opportunity to continuously gather and analyze customer feedback, with the goal of identifying and rectifying issues. This paper examines the alternative of replacing traditional customer satisfaction surveys with social media data. To evaluate this approach the following steps were taken, using customer feedback data extracted from Twitter: 1) Applying sentiment to each Tweet to compare the overall sentiment across different products and/or services. 2) Constructing a hashtag cooccurrence network to further optimize the customer feedback query process from Twitter. 3) Comparing customer feedback from survey responses with social media feedback, while considering content and added value. We find that social media provides advantages over traditional surveys.

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F. Bajic and K. Lyons (2011), "Leveraging Social Media to Gather User Feedback for Software Development", Proceedings of the 2Nd International Workshop on Web 2.0 for Software Engineering
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B. Sumit, L. Jingxuan, S. Tong (2013), "Monitoring and Analyzing Customer Feedback Through Social Media Platforms for Identifying and Remedying Customer Problems", IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp 1147--1154
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cover image ACM Conferences
ASONAM '19: Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
August 2019
1228 pages
ISBN:9781450368681
DOI:10.1145/3341161
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 January 2020

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Author Tags

  1. Twitter
  2. classifier
  3. customers
  4. feedback
  5. machine learning
  6. social media
  7. survey

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ASONAM '19 Paper Acceptance Rate 41 of 286 submissions, 14%;
Overall Acceptance Rate 116 of 549 submissions, 21%

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  • (2024)Fear of Missing Out and Consumption-Sharing Behavior on Social Media: The Moderating Role of Self-Presentation Desire and Social Network TypeSage Open10.1177/2158244024129584714:4Online publication date: 14-Nov-2024
  • (2024)Revealing the sustainable consumption barriers based on the product-service system: social media analytics approachIndustrial Management & Data Systems10.1108/IMDS-03-2023-0199124:12(3240-3273)Online publication date: 9-Sep-2024
  • (2023)Digital Transformation of Ticketing ServicesManagement and Marketing for Improved Retail Competitiveness and Performance10.4018/978-1-6684-8574-3.ch008(156-179)Online publication date: 30-Jun-2023
  • (2023)The Effect of Using Hashtags on Consumer Engagement with The Promotion of Property Products2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS)10.1109/ICIMCIS60089.2023.10349084(61-66)Online publication date: 7-Nov-2023
  • (2023)A Hybrid Framework Using Natural Language Processing and Collaborative Filtering for Performance Efficient Feedback Mining and RecommendationBig Data, Machine Learning, and Applications10.1007/978-981-99-3481-2_40(527-543)Online publication date: 30-Nov-2023
  • (2022)Reviewing the Employee Branding Process to Gain Firm Competitive AdvantageAntecedents and Outcomes of Employee-Based Brand Equity10.4018/978-1-6684-3621-9.ch012(168-185)Online publication date: 17-Jun-2022
  • (2022)Religious Violence and Twitter: Networks of Knowledge, Empathy and FascinationReligions10.3390/rel1303024513:3(245)Online publication date: 12-Mar-2022
  • (2022)Informing Government Decision-Making with Online Citizen Feedback and Social Media: Pedestrianization of Streets2022 IEEE International Symposium on Technology and Society (ISTAS)10.1109/ISTAS55053.2022.10227103(1-7)Online publication date: 10-Nov-2022
  • (2022)New and emerging forms of data and technologies: literature and bibliometric reviewMultimedia Tools and Applications10.1007/s11042-022-13451-582:2(2887-2911)Online publication date: 30-Jul-2022
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