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ORCIDRamya Tekumalla
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2020 – today
- 2023
[j2]Davy Weissenbacher
, Karen O'Connor, Siddharth Rawal, Yu Zhang, Richard Tzong-Han Tsai, Timothy A. Miller, Dongfang Xu, Carol Anderson, Bo Liu, Qing Han, Jinfeng Zhang, Igor Kulev, Berkay Köprü, Raul Rodriguez-Esteban, Elif Ozkirimli, Ammer Ayach, Roland Roller, Stephen R. Piccolo, Peijin Han, V. G. Vinod Vydiswaran, Ramya Tekumalla, Juan M. Banda, Parsa Bagherzadeh, Sabine Bergler, João Figueira Silva, Tiago Melo Almeida, Paloma Martínez, Renzo M. Rivera Zavala, Chen-Kai Wang, Hong-Jie Dai, Luis Alberto Robles Hernandez, Graciela Gonzalez-Hernandez:
Automatic Extraction of Medication Mentions from Tweets - Overview of the BioCreative VII Shared Task 3 Competition. Database J. Biol. Databases Curation 2023 (2023)- [j1]Ramya Tekumalla, Juan M. Banda:
Using weak supervision to generate training datasets from social media data: a proof of concept to identify drug mentions. Neural Comput. Appl. 35(25): 18161-18169 (2023) - [c7]Ramya Tekumalla, Luis Alberto Robles Hernandez, Juan M. Banda:
Towards automatic identification of self-reported COVID-19 tweets: Introducing a multilingual manually annotated dataset, baseline systems and exploratory evaluations. IEEE Big Data 2023: 3736-3742 - [c6]Ramya Tekumalla, Juan M. Banda:
Leveraging Large Language Models and Weak Supervision for Social Media Data Annotation: An Evaluation Using COVID-19 Self-reported Vaccination Tweets. HCI (50) 2023: 356-366 - [i7]Ramya Tekumalla, Juan M. Banda:
Leveraging Large Language Models and Weak Supervision for Social Media data annotation: an evaluation using COVID-19 self-reported vaccination tweets. CoRR abs/2309.06503 (2023) - 2022
- [c5]Ramya Tekumalla, Juan M. Banda:
TweetDIS: A Large Twitter Dataset for Natural Disasters Built using Weak Supervision. IEEE Big Data 2022: 4816-4823 - [c4]Ramya Tekumalla, Juan M. Banda:
An Empirical Study on Characterizing Natural Disasters in Class Imbalanced Social Media Data using Weak Supervision. IEEE Big Data 2022: 4824-4832 - [c3]Ramya Tekumalla, Zia Baig, Michelle Pan, Luis Alberto Robles Hernandez, Michael Wang, Juan M. Banda:
Characterizing Anti-Asian Rhetoric During The COVID-19 Pandemic: A Sentiment Analysis Case Study on Twitter. ICWSM Workshops 2022 - [i6]Ramya Tekumalla, Juan M. Banda:
TweetDIS: A Large Twitter Dataset for Natural Disasters Built using Weak Supervision. CoRR abs/2207.04947 (2022) - [i5]Ramya Tekumalla, Juan M. Banda:
Identifying epidemic related Tweets using noisy learning. CoRR abs/2209.12614 (2022) - 2020
- [c2]Ramya Tekumalla, Juan M. Banda:
Characterizing drug mentions in COVID-19 Twitter Chatter. NLP4COVID@EMNLP 2020 - [c1]Ramya Tekumalla, Javad Rafiei-Asl, Juan M. Banda:
Mining Archive.org's Twitter Stream Grab for Pharmacovigilance Research Gold. ICWSM 2020: 909-917 - [i4]Ramya Tekumalla, Juan M. Banda:
Social Media Mining Toolkit (SMMT). CoRR abs/2003.13894 (2020) - [i3]Ramya Tekumalla, Juan M. Banda:
A large-scale Twitter dataset for drug safety applications mined from publicly existing resources. CoRR abs/2003.13900 (2020) - [i2]Juan M. Banda, Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Gerardo Chowell:
A large-scale COVID-19 Twitter chatter dataset for open scientific research - an international collaboration. CoRR abs/2004.03688 (2020) - [i1]Ramya Tekumalla, Juan M. Banda:
Characterization of Potential Drug Treatments for COVID-19 using Social Media Data and Machine Learning. CoRR abs/2007.10276 (2020)
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