Text Mining in Social Networks

2011 ◽  
pp. 353-378 ◽  
Author(s):  
Charu C. Aggarwal ◽  
Haixun Wang
Keyword(s):  
Social Networks ◽  
Text Mining

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.

A text mining methodology for hot topic detection in social networks

2017 ◽  
Author(s):  
Flora Amato ◽  
Giovanni Cozzolino ◽  
Antonino Mazzeo ◽  
Antonio Pizzata
Keyword(s):  
Social Networks ◽  
Text Mining ◽  
Topic Detection

scholarly journals Questions and features of automated social networks monitoring with support of intelligent user messages analysis.

2014 ◽  
Vol 2014 (4) ◽  
pp. 146-152 ◽  
Author(s):  
Александр Подвесовский ◽  
Aleksandr Podvesovskiy ◽  
Дмитрий Будыльский ◽  
Dmitriy Budylskiy
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Text Mining ◽  
Sentiment Analysis ◽  
Opinion Mining ◽  
Software Implementation ◽  
Network Data ◽  
Research Directions ◽  
Social Network Data ◽  
Monitoring Model

An opinion mining monitoring model for social networks introduced. The model includes text mining processing over social network data and uses sentiment analysis approach in particular. Practical usage results of software implementation and its requirements described as well as further research directions.

Text Mining Using Twitter Data

2021 ◽  
pp. 29-49
Author(s):  
Falak Bhardwaj ◽  
Pulkit Arora ◽  
Gaurav Agrawal
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Text Mining ◽  
Social Networking ◽  
Internet Access ◽  
Social Networking Service ◽  
Twitter Data ◽  
Different Types ◽  
Subject And Object ◽  
Pros And Cons

The microblogging social networking service Twitter has been abuzz around the globe in the last decade. A number of allegations as well as exculpation of different types are being held against it. The list of pros and cons of social networks is huge. India on one hand had an abundance of internet access in last half of the decade. The growth of social media and its influence on people have affected the society in both good as well as in bad way. The following research was done in the month of September and October. The research was carried out on 13 lakh tweets approximately, collected over the course of a month from September to October providing insights about the different attributes of general tweets available on Twitter API for analysis. Insights include the hashtags, account mentions, sentiment, polarity, subject, and object of a tweet. The topics like Rhea Chakraborty and Sushant Singh Rajput, PM Narendra Modi's Birthday, IPL 2020 overshadowed the topics like COVID-19 and women's security.

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