This project was informed by the excellent papers listed below. I am very appreciative of all the authors for inspiring my project. I would also like to thank three professors at GWU whose classes were intrumental in giving me the skills to complete this project, Prof Neil Johnson, Network Analysis for Data Science, Prof. Steven Kunath, Natural Language Processing, and especially Prof. Nima Zahadat, Visualization of Complex Datasets, who also oversaw this research project.
Bohlin, L., Edler, D., Lancichinetti, A., & Rosvall, M. (2014). Community Detection and Visualization of Networks with the Map Equation Framework. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring Scholarly Impact (pp. 3–34). Springer International Publishing. https://doi.org/10.1007/978-3-319-10377-8_1
Boydstun, A., Hardy, A., & Walgrave, S. (2014). Two Faces of Media Attention: Media Storm Versus Non-Storm Coverage. Political Communication, 31. https://doi.org/10.1080/10584609.2013.875967
Hamborg, F., Breitinger, C., & Gipp, B. (2019). Giveme5W1H: A Universal System for Extracting Main Events from News Articles. ArXiv:1909.02766 [Cs]. http://arxiv.org/abs/1909.02766
Hamborg, F., Meschenmoser, P., Schubotz, M., & Gipp, B. (2019). NewsDeps: Visualizing the Origin of Information in News Articles. ArXiv:1909.10266 [Cs]. http://arxiv.org/abs/1909.10266
Herrera-Cubides, J. F., Gaona-García, P. A., & Sánchez-Alonso, S. (2020). Open-Source Intelligence Educational Resources: A Visual Perspective Analysis. Applied Sciences, 10(21), 7617. https://doi.org/10.3390/app10217617
Hogenboom, F., Frasincar, F., Kaymak, U., & de Jong, F. (n.d.). An Overview of Event Extraction from Text. 10.
Mitri, M. (2020). Story Analysis Using Natural Language Processing and Interactive Dashboards. Journal of Computer Information Systems, 0(0), 1–11. https://doi.org/10.1080/08874417.2020.1774442
Nicholls, T., & Bright, J. (2019). Understanding News Story Chains using Information Retrieval and Network Clustering Techniques. Communication Methods and Measures, 13(1), 43–59. https://doi.org/10.1080/19312458.2018.1536972
Ojo, A., & Heravi, B. (2018). Patterns in Award Winning Data Storytelling. Digital Journalism, 6(6), 693–718. https://doi.org/10.1080/21670811.2017.1403291
Rosvall, M., & Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4), 1118–1123. https://doi.org/10.1073/pnas.0706851105
Shahaf, D., & Guestrin, C. (2010). Connecting the dots between news articles. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’10, 623. https://doi.org/10.1145/1835804.1835884
Shahaf, D., Guestrin, C., & Horvitz, E. (2013). “Metro maps of information” by Dafna Shahaf, Carlos Guestrin and Eric Horvitz, with Ching-man Au Yeung as coordinator. ACM SIGWEB Newsletter, Spring, 4:1-4:9. https://doi.org/10.1145/2451836.2451840
Shahaf, D., Guestrin, C., & Horvitz, E. (2012). Trains of thought: Generating information maps. Proceedings of the 21st International Conference on World Wide Web - WWW ’12, 899–908. https://doi.org/10.1145/2187836.2187957
Soelistio, Y., & Surendra, M. (2013, May 15). Simple Text Mining for Sentiment Analysis of Political Figure Using Naive Bayes Classifier Method. https://doi.org/10.12962/p9772338185001.a18
The Guardian—Open Platform. (n.d.). Retrieved May 3, 2021, from https://open-platform.theguardian.com/
theguardian / open platform—Documentation / overview. (n.d.). Retrieved May 3, 2021, from https://open-platform.theguardian.com/documentation/
Zhu, X., & Oates, T. (2012). Finding story chains in newswire articles. 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI), 93–100. https://doi.org/10.1109/IRI.2012.6302996