Online social networks (OSNs) have become a powerful tool to study collective human responses to extreme events such as earthquakes. Most previous research concentrated on a single platform and utilized users’ behaviors on a single platform to study people’s general responses. In this study, we explore the characteristics of people’s behaviors on different OSNs and conduct a cross-platform analysis of public responses to earthquakes. Our findings support the Uses and Gratification theory that users on Reddit and Twitter are engaging with platforms that they may feel best reflect their sense of self. Using the 2019 Ridgecrest earthquakes as our study cases, we collected 510,579 tweets and 45,770 Reddit posts (including 1437 submissions and 44,333 comments) to answer the following research questions: (1) What were the similarities and differences between public responses on Twitter and Reddit? (2) Considering the different mechanisms of Twitter and Reddit, what unique information of public responses can we learn from Reddit as compared with Twitter? By answering these research questions, we aim to bridge the gap of cross-platform public responses research towards natural hazards. Our study evinces that the users on the two different platforms have both different topics of interest and different sentiments towards the same earthquake, which indicates the necessity of investigating cross-platform OSNs to reveal a more comprehensive picture of people’s general public responses towards certain disasters. Our analysis also finds that r/conspiracy subreddit is one of the major venues where people discuss the 2019 Ridgecrest earthquakes on Reddit and different misinformation/conspiracies spread on Twitter and Reddit platforms (e.g., “Big one is coming” on Twitter and “Nuclear test” on Reddit).

Electric vehicles have gained significant popularity in the market, with sales increasing yearly. The introduction of new policies and reforms aimed at promoting environmental sustainability, coupled with the release of more advanced electric vehicles with higher driving ranges and technical specifications, has encouraged more people to consider switching to electric vehicles. However, there is still a lack of understanding of public perception and the factors influencing the decision to switch to electric vehicles, especially among people from different demographic groups. In this study, we leverage machine learning techniques to analyze public opinion about electric vehicles across different demographic groups on two online social networks (OSNs), namely Reddit and Twitter. Our analyses provide valuable insights into how users on these platforms perceive electric vehicles and the factors that influence their perception. This information can be used to inform market strategies and future policies aimed at promoting the adoption of electric vehicles.

This paper investigates the commercial viability of and public attitudes towards dynamic wireless charging technology. A cost model that calculates the overall lifecycle cost of ownership for electric vehicles equipped with dynamic charging capabilities is built using both real-world data and realistic assumptions. Results from this model indicate that increasing the penetration of electric vehicles (EVs) on U.S. roadways will rapidly reduce dynamic charging costs. Under certain realistic conditions, a nation-wide breakeven point between dynamic and at-home charging can be achieved at ~21% EV penetration. State-level analyses suggest that Hawaii, California, and the Northeast states have the greatest potential for mass wireless power transfer (WPT) adoption in the near future. Furthermore, the public perception of wireless charging is studied through a sentiment analysis of Twitter data from 2018-2022. WPT-related posts on Twitter are extracted and collated into a dataset of 46,618 tweets. To the authors’ best knowledge, this is the first and largest WPT-specific corpus. Sentiment analysis results indicate that the frequency with which dynamic wireless charging is being discussed increased drastically over the study period, while the sentiment with which it is being discussed has remained mildly positive.