Publications

We’re always building new collaborations and publishing new projects. These are a few of the peer-reviewed studies and preprints published by members of our team during their time in The Computational Media Lab.

Articles/Papers/Proceedings (* indicates student author):

• Kolluri, A.*, Vinton, K.*, and Murthy, D. PoxVerifi: An Information Verification System to Combat Monkeypox Misinformation, arXiv, 2023

• Murthy, D., Caramanis, C., and Rudra, K., Understanding Lexical Biases when Identifying Gang-related Social Media Communications, arXiv, 2023.

• Murthy, D., Dasari, T.*, Vinton, K.*, Lago Arroyo, F.*, Li, C.* and Clayton, P., Using Machine Learning, Social Media Images, and Journalists to Improve Disaster Resilience and Response. SSRN, 2023.

• Shankar, S.*, Murthy, D., Dashtian, H., Social Media COVID-19 Contact Tracing Using Mobile Social Payments and Facebook Data, arXiv, 2023

• Stobaugh, B.* and Murthy, D., Predicting Gender and Political Affiliation Using Mobile Payment Data, arXiv, 2023.

• Norton, E.*, Thomas, T.*, Kolluri, A.*, Kim, T.H.*, Murthy, D., Temporal Analysis of Misinformation on Parler, arXiv, 2023.

Venkatesh, P.*, Kolluri, A.*, Kolluri, N. L.*, and Murthy D. Using Network Analysis to Characterize Racist Parler Users. Longhorn Research Poster Session 2022.

• Kolluri, N.L.*, Liu, Y.*, and Murthy, D. COVID-19 Misinformation Detection: Machine Learned Solutions to the Infodemic, JMIR Infodemiology, 2022;2(2):e38756, 2022. [Demo Video] [Creator Interview] [Blog]

• Aguiar, I.*, Yoo, Joseph J.*, and Murthy, D., Make Tweets Great Again: Who are opinion leaders, and what did they tweet about Donald Trump?‘, Social Science Computer Review, accepted, in press, available online.

• Dashtian H., Murthy, D., and and Kong G., An exploration of e-cigarette-related search items on YouTube‘, Journal of Medical Internet Research, 24(1):e30679, 2022.

• Murthy, D., Kolluri, N. L., Dashtian, H., CoVerifi: A COVID-19 news verification system – Tool Demonstration, Knight Research Network Tool Demonstration Day, October 13, 2021.

• Kolluri, N. L.* and Murthy, D., CoVerifi: A COVID-19 News Verification System‘, Online Social Networks and Media, Vol. 22: Article 100123: 1-13, 2021. (pre-print PDF) (PDF at publisher)

• Dashtian, H. and Murthy, D., CML-COVID: A Large-Scale COVID-19 Twitter dataset with Latent Topics, Sentiment and Location Information‘, Academia Letters , Article 314: 1-9, 2021. (open-access PDF at publisher, local PDF)

• Devaraj, A.*, Murthy, D. and Dontula, A.*, Machine-learning methods for identifying social media-based requests for urgent help during hurricanes, International Journal of Disaster Risk Reduction. Vol. 51: Article 101757: 1-12, 2020. (PDF).

• Unger, C., Murthy, D., Acker, A., Arora, I., and Chang, A.Y., Examining the evolution of mobile social payments in Venmo. Proceedings of the 11th International Conference on Social Media and Society (ACM SMSociety 20); pp. 101–110. (Pre-Print PDF).

• Murthy, D., Sudarshan, S.*, Lee, J.*, Ghosh, C.*, Shah, P.*, Xiao, W.J.*, Arora, I.*, Unger, C.*, and Acker, A.*, Understanding the Meaning of Emoji in Mobile Social Payments, Big Data & Society, in press.

• Johnson, M.*, Murthy, D., Robertson, B. W.*, Smith, W. R.*, & Stephens, K. K. (2020). DisasterNet: Evaluating the performance of transfer learning to classify hurricane-related images posted on Twitter. Proceedings of the 53rd Annual Hawaii International Conference on Social Systems, Computer Society Press.  Maui, Hawaii, pp. 576-583. (PDF)

• Robertson, B. W.*, Johnson, M.*, Murthy, D., Smith, W. R.*, & Stephens, K. K. (2019). Using a combination of human insights and ‘deep learning’ for real-time disaster communication. Progress in Disaster Science. Volume 2, July 2019, 100030: 1-11. [PDF]

• Johnson, M.*, Murthy, D., Robertson, B.W.*, Smith, R.*, Stephens, K.K.. In Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM), Polytechnic University of Valencia, Valencia, Spain, pp. 1375-1376. [PDF]

• Xin, E.*, Murthy, D., Lakuduva, N.*, & Stephens, K. K. Assessing the stability of Tweet corpora for hurricane events over time: A mixed methods approach.   in Proceedings of the 10th International Conference on Social Media and Society (ACM SMSociety ’19), Ryerson University, Toronto, Canada, pp. 59-66. (PDF)

• Stephens, K. K., Robertson & Murthy, D. Throw Me a Lifeline: Articulating Mobile Social Network Dispersion and the Social Construction of Risk In Rescue Communication. Mobile Media & Communication, Accepted; available online. [PDF]

• O’Neal, A.*, Rodgers, B.*, Segler, J.*, Murthy, D.,  Lakuduva, N.*, Johnson, M.*, Stephens, K. (2018) ‘Training an Emergency-Response Image Classifier on Signal Data‘ In Kantardzic & Sayed-Mouchaweh (Eds.), Proceedings of the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA’18).  Orlando, FL,  December 2018. (PDF)

• Acker, A. and Murthy, D. (2018) ‘Venmo: Understanding mobile payments as social media‘, Proceedings of the 9th International Conference on Social Media and Society. Copenhagen, Denmark, July 18 – 20, pp. 5-12, 2018. (PDF)

• Stephens, K. K., Li, J.*, Robertson, B. W.*, Smith, W. R.* & Murthy, D. (2018) ‘Citizens communicating health information: Urging others in their community to seek help during a flood‘ in K. Boersma & B. Tomaszewski (Eds.) Proceedings of the 15th International ISCRAM Conference. Rochester, NY, 2018. (PDF)

• Smith, W. R.*, Stephens, K. K., Robertson, B. W.*, Li. J.*, & Murthy, D. (2018) ‘Social media in citizen-led disaster response: Rescuer roles, coordination challenges, and untapped potential‘ in K. Boersma & B. Tomaszewski (Eds.) Proceedings of the 15th International ISCRAM Conference. Rochester, NY, 2018. (PDF)

Posters (* indicates student author):

• Keshari, S.*, Anand, T.*, Lee, J., Ouellette, R., Murthy, D. , Kong, G., Large Cigar Detection using Computer Vision, Annual Meeting of the Society for Research on Nicotine and Tobacco, San Antonio, TX, March 2023. (PDF)

• Anand, T.*, Ouellette, R., Lee, J., Murthy, D., Kong, G., Using automatic clustering to identify themes from vape-related content on TikTok, Annual Meeting of the Society for Research on Nicotine and Tobacco, San Antonio, TX, March 2023. (PDF)

• Anand, T.*, Radhakrishnan, N.*, Mohan, C.*, Lee, J., Ouellette, R. Murthy, D., Kong, G., Leveraging computer vision frameworks to automatically identify e-cigarette content on TikTok posts, Annual Meeting of the Society for Research on Nicotine and Tobacco, San Antonio, TX, March 2023. (PDF)

• Vinton, K.*, Anand, T.*, Ouellette, R., Lee, J., Murthy, D., Kong, G., Testing the TikTok algorithm: Can underage TikTok users elicit e-cigarette content recommendations?, Annual Meeting of the Society for Research on Nicotine and Tobacco, San Antonio, TX, March 2023. (PDF)