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GLaSS: Semi-supervised Graph Labelling with Markov Random Walks to Absorption., , , and . COMPLEX NETWORKS (1), volume 812 of Studies in Computational Intelligence, page 304-315. Springer, (2018)The one comparing narrative social network extraction techniques., , , and . CoRR, (2018)Estimating the Parameters of the Waxman Random Graph., , and . WAW, volume 11631 of Lecture Notes in Computer Science, page 71-86. Springer, (2019)Pachinko Prediction: A Bayesian method for event prediction from social media data., , , , , , and . Inf. Process. Manag., 57 (2): 102147 (2020)Podlab at SemEval-2019 Task 3: The Importance of Being Shallow., , , , and . SemEval@NAACL-HLT, page 292-296. Association for Computational Linguistics, (2019)Semi-supervised graph labelling reveals increasing partisanship in the United States Congress., , , and . Appl. Netw. Sci., 4 (1): 62:1-62:18 (2019)The one comparing narrative social network extraction techniques., , , and . ASONAM, page 905-913. IEEE, (2020)A framework for streamlined statistical prediction using topic models., , , and . LaTeCH@NAACL-HLT, page 61-70. Association for Computational Linguistics, (2019)Rasch Analysis of HTTPS Reachability., , , , and . Networking, page 1-9. IFIP, (2018)BREADR: An R Package for the Bayesian Estimation of Genetic Relatedness from Low-coverage Genotype Data., , , and . J. Open Source Softw., 10 (109): 7916 (May 2025)