Skip to content

Latest commit

 

History

History
49 lines (34 loc) · 2.33 KB

README.md

File metadata and controls

49 lines (34 loc) · 2.33 KB
Raw

ConStory: Automatic story investigator of public perception on the mega urban infrastructure project

A project focused on extracting the public opinions of North Houston Highway Improvement Project (IH-45) from Twitter

  • Copyright (C) 2022 The University of Texas at Arlington
  • Copyright (C) 2022 HBE: The Humanized Built Environment, (https://hubilab.uta.edu/)
  • Copyright (C) 2022 Alireza Shamshiri, Kyeong Rok Ryu, Steven McCullough, and June Young Park

Citation of this project

  • Alireza Shamshiri, Kyeong Rok Ryu, Steven McCullough, and June Young Park. 2022. ConStory: Automatic story investigator of public perception on the mega urban infrastructure project: poster abstract. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys '22). Association for Computing Machinery, New York, NY, USA, 293–294. https://doi.org/10.1145/3563357.3567751

Data collection & Preprocessing

  • 4103 Scrapped Tweets from Twitter
  • Text preprocessing has been done using Natural Language Toolkit (NLTK)

Topic Modeling

Temporal Analysis of Tweets

- Number of Tweets between 2008 and 2021, Bottom: Most used words in posted tweets for each phase

Topic Modeling Results

- Weights of extracted topics based on the appearing in the number of tweets posted in each year
  • Topic Weights = Number of topics assigned to each tweet / Each year tweets contain that topic

Citation

If you liked our paper, please consider citing it

@inproceedings{shamshiri2022constory,
  title={ConStory: Automatic story investigator of public perception on the mega urban infrastructure project},
  author={Shamshiri, Alireza and Ryu, Kyeong Rok and McCullough, Steven and Park, June Young},
  booktitle={Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation},
  pages={293--294},
  year={2022}
}