Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data
The purpose of this article is to present a framework for capturing and analyzing social media posts using a sentiment analysis tool to determine the views of the general public towards autonomous mobility. The paper presents the systems used and the results of this analysis, which was performed on...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Logistics |
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| Online Access: | https://www.mdpi.com/2305-6290/4/2/12 |
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| author | Nikolaos Bakalos Nikolaos Papadakis Antonios Litke |
| author_facet | Nikolaos Bakalos Nikolaos Papadakis Antonios Litke |
| author_sort | Nikolaos Bakalos |
| collection | DOAJ |
| description | The purpose of this article is to present a framework for capturing and analyzing social media posts using a sentiment analysis tool to determine the views of the general public towards autonomous mobility. The paper presents the systems used and the results of this analysis, which was performed on social media posts from Twitter and Reddit. To achieve this, a specialized lexicon of terms was used to query social media content from the dedicated application programming interfaces (APIs) that the aforementioned social media platforms provide. The captured posts were then analyzed using a sentiment analysis framework, developed using state-of-the-art deep machine learning (ML) models. This framework provides labeling for the captured posts based on their content (i.e., classifies them as positive or negative opinions). The results of this classification were used to identify fears and autonomous mobility aspects that affect negative opinions. This method can provide a more realistic view of the general public’s perception of automated mobility, as it has the ability to analyze thousands of opinions and encapsulate the users’ opinion in a semi-automated way. |
| format | Article |
| id | doaj-art-8a1fc06ca29a4a4da354f74cb20b903e |
| institution | Kabale University |
| issn | 2305-6290 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Logistics |
| spelling | doaj-art-8a1fc06ca29a4a4da354f74cb20b903e2025-08-20T03:35:23ZengMDPI AGLogistics2305-62902020-06-01421210.3390/logistics4020012Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media DataNikolaos Bakalos0Nikolaos Papadakis1Antonios Litke2Survey Engineering, National Technical University of Athens, Zografou Campus 9, Iroon Polytechniou str, Zografou, 15780 Athens, GreeceResearch and Innovation, Infili Technologies PC, 60 Kousidi st, 15772 Athens, GreeceResearch and Innovation, Infili Technologies PC, 60 Kousidi st, 15772 Athens, GreeceThe purpose of this article is to present a framework for capturing and analyzing social media posts using a sentiment analysis tool to determine the views of the general public towards autonomous mobility. The paper presents the systems used and the results of this analysis, which was performed on social media posts from Twitter and Reddit. To achieve this, a specialized lexicon of terms was used to query social media content from the dedicated application programming interfaces (APIs) that the aforementioned social media platforms provide. The captured posts were then analyzed using a sentiment analysis framework, developed using state-of-the-art deep machine learning (ML) models. This framework provides labeling for the captured posts based on their content (i.e., classifies them as positive or negative opinions). The results of this classification were used to identify fears and autonomous mobility aspects that affect negative opinions. This method can provide a more realistic view of the general public’s perception of automated mobility, as it has the ability to analyze thousands of opinions and encapsulate the users’ opinion in a semi-automated way.https://www.mdpi.com/2305-6290/4/2/12sentiment analysisacceptance of autonomous mobilitymachine learningsocial media mining |
| spellingShingle | Nikolaos Bakalos Nikolaos Papadakis Antonios Litke Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data Logistics sentiment analysis acceptance of autonomous mobility machine learning social media mining |
| title | Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data |
| title_full | Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data |
| title_fullStr | Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data |
| title_full_unstemmed | Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data |
| title_short | Public Perception of Autonomous Mobility Using ML-Based Sentiment Analysis over Social Media Data |
| title_sort | public perception of autonomous mobility using ml based sentiment analysis over social media data |
| topic | sentiment analysis acceptance of autonomous mobility machine learning social media mining |
| url | https://www.mdpi.com/2305-6290/4/2/12 |
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