GTdownloader: A Python Package to Download, Visualize, and Export Georeferenced Tweets From the Twitter API

Acosta-Sequeda, Juan; Derrible, Sybil

doi:10.5334/jors.443

Cited by 2 publications

References 12 publications

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Temporal public perceptions and experiences during water service disruptions: the case of Jackson, Mississippi

Safarpour,

Spearing

2024

Environ. Res.: Infrastruct. Sustain.

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Failures in urban water systems are becoming a common occurrence in the US due to disasters, aging infrastructure, and financial constraints, among other concerns. For example, Jackson, Mississippi has experienced reoccurring water outages, burdening community members as they must seek alternative water sources. Prior research has primarily focused on technical, institutional, and public health aspects of water crises, with limited attention to community perspectives. Understanding such social aspects can shed light on, for example, community priorities, levels of trust, mental health concerns, and communication gaps. Here, we document the temporal experiences and perceptions of community members during the Jackson Water Crises. To do so, we qualitatively analyzed news media data and employed topic modeling techniques on social media data from two years, capturing two specific crises. Our results reveal the cascading impacts of water outages on end-users, including financial, social, and technical issues. For example, over time, results indicate that trust in the government and water providers in Jackson eroded, which may hinder public support. Our results show that social media can be a useful tool for utilities to understand public perceptions in real-time. Recommendations proposed here can inform future responses to water crises in Jackson and other communities, ensuring end-users perspectives are incorporated.

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Temporal public perceptions and experiences during water service disruptions: the case of Jackson, Mississippi

Safarpour,

Spearing

2024

Environ. Res.: Infrastruct. Sustain.

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Estimating Telecommuting Rates in the US Using Twitter Sentiment Analysis

Acosta-Sequeda,

Mohammadi,

Patipati

et al. 2024

Preprint

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The COVID-19 pandemic had a significant impact on virtually every human activity. Millions of workers around the globe from eligible professions stayed at home working as part of the measures taken to contain the virus’ spread. The change in transportation demand associated to this phenomenon poses a challenge for cities, especially regarding public transportation, where the decrease in demand arose critical questions on how to assess decreased ridership and potential rebound effects. With this in mind, we ask: can we obtain real-time demand change estimates using social media data? Hence, the aim of this work is to take social media unstructured information and transform it into structured insights that can offer almost real-time estimates on demand trends associated with telecommuting. To achieve this, we obtained around 50,000 geo-tagged tweets relevant to telecommuting in the US. With that, we leveraged transformers Machine Learning methods to fine-tune a language model capable of automatically assigning a sentiment to tweets on this topic. We used the time evolution of the obtained sentiments as covariates in time series forecasting models to estimate telecommuting rates at both the national and state levels, observing a drastic improvement over the estimates without such covariates. Our major finding indicates that it is possible to structure social media data in order to use it to obtain demand change estimates, and that the accuracy of such estimates is going to depend heavily on how much people discuss the topic in question in a determined geography. This finding is in line with others that have found alternative ways of obtaining insights on transportation data, and hence, is a relevant contribution towards real-time data-driven approaches for transportation demand assessment.

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GTdownloader: A Python Package to Download, Visualize, and Export Georeferenced Tweets From the Twitter API

Cited by 2 publications

References 12 publications

Temporal public perceptions and experiences during water service disruptions: the case of Jackson, Mississippi

Temporal public perceptions and experiences during water service disruptions: the case of Jackson, Mississippi

Estimating Telecommuting Rates in the US Using Twitter Sentiment Analysis

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