scholarly journals Text Mining by Social Network Data towards Developing Attractiveness of Urban Park. Case Study: Thematic Parks in Bandung City, Indonesia

2021 ◽  
Vol 738 (1) ◽  
pp. 012057
Author(s):  
Munawir ◽  
Lia Nurbanillah Fujianti ◽  
M D Koerniawan ◽  
Bart Dewancker
Keyword(s):  
Social Network ◽  
Text Mining ◽  
Urban Park ◽  
Network Data ◽  
Social Network Data

scholarly journals Online Data Preprocessing: A Case Study Approach

2019 ◽  
Vol 9 (4) ◽  
pp. 2620
Author(s):  
Mohammed Zuhair Al-Taie ◽  
Seifedine Kadry ◽  
Joel Pinho Lucas
Keyword(s):  
Social Network ◽  
Data Preprocessing ◽  
Quality Data ◽  
The Internet ◽  
Network Data ◽  
Quality Of Data ◽  
Standard Format ◽  
Social Network Data

<span lang="EN-US">Besides the Internet search facility and e-mails, social networking is now one of the three best uses of the Internet. A tremendous number of volunteers every day write articles, share photos, videos and links at a scope and scale never imagined before. However, because social network data are huge and come from heterogeneous sources, the data are highly susceptible to inconsistency, redundancy, noise, and loss. For data scientists, preparing the data and getting it into a standard format is critical because the quality of data is going to directly affect the performance of mining algorithms that are going to be applied next. Low-quality data will certainly limit the analysis and lower the quality of mining results. To this end, the goal of this study is to provide an overview of the different phases involved in data preprocessing, with a focus on social network data. As a case study, we will show how we applied preprocessing to the data that we collected for the Malaysian Flight MH370 that disappeared in 2014.</span>

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.

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