Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 25, 20 December 2023
Open
Access | Article
Evaluating random sampling bias in sentiment analysis of social media data
* Author to whom correspondence should be addressed.
Abstract
In this age marked by a wealth of information, the relevance of social networks has increased in a manner that is analogous to an exponential growth curve. Notably, the content that is shared on these platforms has the potential to act as a reflection of the emotional states that people are now experiencing. The importance of emotions is brought to light in the research presented here, which makes use of a technique based on a review of the relevant literature to analyze the problem of random sample bias and the effects that it has on sentiment analysis. It is possible to draw the conclusion, on the basis of the findings of the research, that the problem of random sample propensity is not a sporadic or insignificant one. In addition, the findings of the study indicate the presence of multiple types of prejudice. Because of the potential repercussions that could result from doing a distorted sentiment analysis, it is really necessary to keep your method focused.
Keywords
Social Media Data, Random Sampling Bias, Sentiment Analysis
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-233-6
- ISBN (Online)
- 978-1-83558-234-3
- Published Date
- 20 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/25/20240895
- Copyright
- 20 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited