Profile matching of online users across multiple social networks: A text mining approach

2022 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Basav Roychoudhury ◽  
Deepesh Kumar Srivastava
Keyword(s):  
Social Networks ◽  
Text Mining ◽  
Profile Matching

Negative Customer Experience in Lifestyle Hotels

2021 ◽  
pp. 126-157
Author(s):  
Manoel Vitor Santos ◽  
Amélia M. P. C. Brandão
Keyword(s):  
Social Networks ◽  
Text Mining ◽  
Consumer Behaviour ◽  
Online Reviews ◽  
Customer Experience ◽  
Customer Complaints ◽  
Online Platforms ◽  
Hotel Service ◽  
Hotel Managers

The primary purpose of the present research is to develop a methodology which can accurately analyse online public reviews on Google using Netnography studies combined with text mining analyses. By analysing the current techniques applied to a lifestyle hotel brand in nine properties in different countries and carefully studying how negative reviews are expressed online by costumers, this study aims to create a pattern of lifestyle customer complaints. This research seeks to demonstrate patterns of consumer behaviour that are not fully satisfied with the hotel service and how it can negatively affect the brand. This study identifies the areas that five stars lifestyle hoteliers and hotel managers need to pay attention to improve services, considering online reviews on online platforms, such as social networks and other tourism sites. Today, online reviews and customer experiences have a significant impact on the choice of a hotel.

scholarly journals Factor Graph Model Based User Profile Matching Across Social Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 152429-152442
Author(s):  
Lidong Wang ◽  
Keyong Hu ◽  
Yun Zhang ◽  
Shihua Cao
Keyword(s):  
Social Networks ◽  
Graph Model ◽  
User Profile ◽  
Factor Graph ◽  
Model Based ◽  
Profile Matching ◽  
Factor Graph Model
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