Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society

Sungjoon Cho

doi:doi:10.11648/j.ijdsa.20210703.14

| Peer-Reviewed

Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society

Sungjoon Cho

Published in International Journal of Data Science and Analysis (Volume 7, Issue 3)

Received: 26 April 2021 Accepted: 12 May 2021 Published: 31 May 2021

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

In recent decades, the development of technology has brought several changes in the global society. Enhanced communication methods enabled rapid dissemination of information, impacting peoples’ decision making and consumption. Moreover, indiscreet production and resource consumption caused environmental damage, hence leading to the advent of electric vehicles in the automotive industry. This research paper delves into the influence of social media on market share and stock prices of electric vehicle manufacturers. Social media plays a significant role in conveying information and therefore influencing consumption. To conduct research, we gathered data – tweets, news articles, EV stock prices, EV market shares, air quality of major cities – to prove correlation between social media and EV stock prices. Market data were mainly used for analysis and prediction, and information regarding air quality was used to explain how electric vehicles could gather huge momentum. We analyzed how electric vehicle market shares have changed in 10 years, and how individual manufacturers, such as Tesla, General Motors, and Hyundai, increased production and sales over time, using data analysis and visualization. By comparing these data with media coverage of electric vehicles using sentimental analysis, we could figure out how social media could impact sales and stock prices of automotive producers. The main driving force of the meteoric rise of electric vehicles was favorable media coverage of electric vehicles. Data collection was done by effective Python tools that could significantly reduce time.

Published in	International Journal of Data Science and Analysis (Volume 7, Issue 3)
DOI	10.11648/j.ijdsa.20210703.14
Page(s)	76-81
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Electric Vehicles, Sentimental Analysis, Machine Learning, Data Analysis

References

[1]	D. Romero, and A. Molina, “Towards a sustainable development maturity model for green virtual enterprise breeding enviornments,” Proceedings of the 19th IFAC World Congress, 2014.
[2]	D. Den, “Analyzing Scientific Papers Based on Sentiment Analysis”, Cairo University, January 2016.
[3]	B. Norm, E. Lett, and C. Villegas, “Sentiment analysis and opinion mining applied to scientific paper reviews”, Intelligent Data Analysis, February 2019.
[4]	S. Gupta, “Sentiment Analysis: Concept, Analysis and Applications,” Toward Data Science, 2018.
[5]	“Sentiment Analysis Explained”, Lexalytics.
[6]	V. Agar, “Research on Data Preprocessing and Categorization Technique for Smartphone Review Analysis”, International Journal of Computer Applications, 2015.
[7]	A. Kadhim, “An Evaluation of Preprocessing Techniques for Text Classification”, International Journal of Computer Science and Information Security, June 2018.
[8]	W. Wilbur, “The automatic identification of stop words”, Journal of Information Science”, 1992.
[9]	L. Skork, “Application of Lemmatization and Summarization Methods in Topic Identification Module for Large Scale Language Modeling Data Filtering”, 15th International Conference, 2012.
[10]	A. Jivani “A Comparative Study of Stemming Algorithms”, The Maharaja Sayajirao University of Baroda, 2011.
[11]	C. Yu, “E, xploratory data analysis in the context of data mining and resampling”, International Journal of Psychological Research, June 2010.
[12]	C. Moral, A. An, R. Imbert, J. Ramirez “A survey of stemming algorithms in information retrieval”, Information Research, March 2014.
[13]	S. Mal, R. Har, and A. Kun, “XGBoost - A Deep dive into Gradient Boosting (Introduction Documentation)”, Medium, Feburary 2017.
[14]	J. Peng, K. Lee, and G. Ing, “An Introduction to Logistic Regression Analysis and Reporting”, The Journal of Educaitonal Research, Septemper, 2002.
[15]	J. Ali, R. Khan, N. Ahmad, I. Maq “Random Forests and Decision Trees”, International Journal of Computer Science Issues, September, 2012.

Cite This Article

Plain Text BibTeX RIS

APA Style

Sungjoon Cho. (2021). Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. International Journal of Data Science and Analysis, 7(3), 76-81. https://doi.org/10.11648/j.ijdsa.20210703.14

Copy | Download

ACS Style

Sungjoon Cho. Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. Int. J. Data Sci. Anal. 2021, 7(3), 76-81. doi: 10.11648/j.ijdsa.20210703.14

Copy | Download

AMA Style

Sungjoon Cho. Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. Int J Data Sci Anal. 2021;7(3):76-81. doi: 10.11648/j.ijdsa.20210703.14

Copy | Download

@article{10.11648/j.ijdsa.20210703.14,
  author = {Sungjoon Cho},
  title = {Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society},
  journal = {International Journal of Data Science and Analysis},
  volume = {7},
  number = {3},
  pages = {76-81},
  doi = {10.11648/j.ijdsa.20210703.14},
  url = {https://doi.org/10.11648/j.ijdsa.20210703.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20210703.14},
  abstract = {In recent decades, the development of technology has brought several changes in the global society. Enhanced communication methods enabled rapid dissemination of information, impacting peoples’ decision making and consumption. Moreover, indiscreet production and resource consumption caused environmental damage, hence leading to the advent of electric vehicles in the automotive industry. This research paper delves into the influence of social media on market share and stock prices of electric vehicle manufacturers. Social media plays a significant role in conveying information and therefore influencing consumption. To conduct research, we gathered data – tweets, news articles, EV stock prices, EV market shares, air quality of major cities – to prove correlation between social media and EV stock prices. Market data were mainly used for analysis and prediction, and information regarding air quality was used to explain how electric vehicles could gather huge momentum. We analyzed how electric vehicle market shares have changed in 10 years, and how individual manufacturers, such as Tesla, General Motors, and Hyundai, increased production and sales over time, using data analysis and visualization. By comparing these data with media coverage of electric vehicles using sentimental analysis, we could figure out how social media could impact sales and stock prices of automotive producers. The main driving force of the meteoric rise of electric vehicles was favorable media coverage of electric vehicles. Data collection was done by effective Python tools that could significantly reduce time.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society
AU  - Sungjoon Cho
Y1  - 2021/05/31
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdsa.20210703.14
DO  - 10.11648/j.ijdsa.20210703.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 76
EP  - 81
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20210703.14
AB  - In recent decades, the development of technology has brought several changes in the global society. Enhanced communication methods enabled rapid dissemination of information, impacting peoples’ decision making and consumption. Moreover, indiscreet production and resource consumption caused environmental damage, hence leading to the advent of electric vehicles in the automotive industry. This research paper delves into the influence of social media on market share and stock prices of electric vehicle manufacturers. Social media plays a significant role in conveying information and therefore influencing consumption. To conduct research, we gathered data – tweets, news articles, EV stock prices, EV market shares, air quality of major cities – to prove correlation between social media and EV stock prices. Market data were mainly used for analysis and prediction, and information regarding air quality was used to explain how electric vehicles could gather huge momentum. We analyzed how electric vehicle market shares have changed in 10 years, and how individual manufacturers, such as Tesla, General Motors, and Hyundai, increased production and sales over time, using data analysis and visualization. By comparing these data with media coverage of electric vehicles using sentimental analysis, we could figure out how social media could impact sales and stock prices of automotive producers. The main driving force of the meteoric rise of electric vehicles was favorable media coverage of electric vehicles. Data collection was done by effective Python tools that could significantly reduce time.
VL  - 7
IS  - 3
ER  -

Copy | Download

Author Information

Sungjoon Cho

Cheongshim International Academy, Gyeonggi, Republic of Korea

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Sungjoon Cho. (2021). Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. International Journal of Data Science and Analysis, 7(3), 76-81. https://doi.org/10.11648/j.ijdsa.20210703.14

Copy | Download

ACS Style

Sungjoon Cho. Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. Int. J. Data Sci. Anal. 2021, 7(3), 76-81. doi: 10.11648/j.ijdsa.20210703.14

Copy | Download

AMA Style

Sungjoon Cho. Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society. Int J Data Sci Anal. 2021;7(3):76-81. doi: 10.11648/j.ijdsa.20210703.14

Copy | Download

@article{10.11648/j.ijdsa.20210703.14,
  author = {Sungjoon Cho},
  title = {Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society},
  journal = {International Journal of Data Science and Analysis},
  volume = {7},
  number = {3},
  pages = {76-81},
  doi = {10.11648/j.ijdsa.20210703.14},
  url = {https://doi.org/10.11648/j.ijdsa.20210703.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20210703.14},
  abstract = {In recent decades, the development of technology has brought several changes in the global society. Enhanced communication methods enabled rapid dissemination of information, impacting peoples’ decision making and consumption. Moreover, indiscreet production and resource consumption caused environmental damage, hence leading to the advent of electric vehicles in the automotive industry. This research paper delves into the influence of social media on market share and stock prices of electric vehicle manufacturers. Social media plays a significant role in conveying information and therefore influencing consumption. To conduct research, we gathered data – tweets, news articles, EV stock prices, EV market shares, air quality of major cities – to prove correlation between social media and EV stock prices. Market data were mainly used for analysis and prediction, and information regarding air quality was used to explain how electric vehicles could gather huge momentum. We analyzed how electric vehicle market shares have changed in 10 years, and how individual manufacturers, such as Tesla, General Motors, and Hyundai, increased production and sales over time, using data analysis and visualization. By comparing these data with media coverage of electric vehicles using sentimental analysis, we could figure out how social media could impact sales and stock prices of automotive producers. The main driving force of the meteoric rise of electric vehicles was favorable media coverage of electric vehicles. Data collection was done by effective Python tools that could significantly reduce time.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Scientific Data Analysis: Employing Sentimental Analysis to Prove Correlation Between Social Media and Electric Vehicles in Modern Society
AU  - Sungjoon Cho
Y1  - 2021/05/31
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdsa.20210703.14
DO  - 10.11648/j.ijdsa.20210703.14
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 76
EP  - 81
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20210703.14
AB  - In recent decades, the development of technology has brought several changes in the global society. Enhanced communication methods enabled rapid dissemination of information, impacting peoples’ decision making and consumption. Moreover, indiscreet production and resource consumption caused environmental damage, hence leading to the advent of electric vehicles in the automotive industry. This research paper delves into the influence of social media on market share and stock prices of electric vehicle manufacturers. Social media plays a significant role in conveying information and therefore influencing consumption. To conduct research, we gathered data – tweets, news articles, EV stock prices, EV market shares, air quality of major cities – to prove correlation between social media and EV stock prices. Market data were mainly used for analysis and prediction, and information regarding air quality was used to explain how electric vehicles could gather huge momentum. We analyzed how electric vehicle market shares have changed in 10 years, and how individual manufacturers, such as Tesla, General Motors, and Hyundai, increased production and sales over time, using data analysis and visualization. By comparing these data with media coverage of electric vehicles using sentimental analysis, we could figure out how social media could impact sales and stock prices of automotive producers. The main driving force of the meteoric rise of electric vehicles was favorable media coverage of electric vehicles. Data collection was done by effective Python tools that could significantly reduce time.
VL  - 7
IS  - 3
ER  -

Copy | Download