Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology 2018
DOI: 10.18287/1613-0073-2018-2212-262-269
|View full text |Cite
|
Sign up to set email alerts
|

Application of the principal component analysis to detect semantic differences during the content analysis of social networks

Abstract: In this paper, we propose an approach to semantic differences detection in texts presented in the form of frequency dictionaries. The original text data has been obtained by collecting records on various online communities. We have implemented a specialized software module that allows us to analyze and download both posts and comments from the social network VK's open communities. To build our frequency dictionary, we have developed an algorithm that takes into account the peculiarities of the data collected f… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2020
2020

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 11 publications
0
1
0
Order By: Relevance
“…To determine the proximity of groups, several metrics for the comparison of word indexes were considered: Euclidean distance, city-block distance and Mahalanobis distance [7,8]. The Euclidean distance was chosen, since it is most suitable for this experiment according to the following criteria:…”
Section: Determination Of the Proximity Of Groups Using Bigdata Technmentioning
confidence: 99%
“…To determine the proximity of groups, several metrics for the comparison of word indexes were considered: Euclidean distance, city-block distance and Mahalanobis distance [7,8]. The Euclidean distance was chosen, since it is most suitable for this experiment according to the following criteria:…”
Section: Determination Of the Proximity Of Groups Using Bigdata Technmentioning
confidence: 99%