Update README.md

README.md

@@ -11,7 +11,7 @@ language:
 
 ### Dataset Summary
 
-This dataset is a compilation of several existing datasets focused on misinformation detection, disaster-related tweets, and fact-checking. It combines data from multiple sources to create a comprehensive dataset for training misinformation detection models.
+This dataset is a compilation of several existing datasets focused on misinformation detection, disaster-related tweets, and fact-checking. It combines data from multiple sources to create a comprehensive dataset for training misinformation detection models. This dataset has been utilized in research studying backdoor attacks in textual content, notably in "Claim-Guided Textual Backdoor Attack for Practical Applications" (Song et al., 2024).
 
 ### Supported Tasks and Leaderboards
 
@@ -194,6 +194,22 @@ Note: This dataset is intended for academic and non-commercial use only, in comp
 
 ### Citation Information
 
+If you use this dataset in your research, please cite both the original source datasets and any relevant papers using this compiled dataset:
+
+Research Using This Dataset:
+```bibtex
+@misc{song2024claimguidedtextualbackdoorattack,
+      title={Claim-Guided Textual Backdoor Attack for Practical Applications}, 
+      author={Minkyoo Song and Hanna Kim and Jaehan Kim and Youngjin Jin and Seungwon Shin},
+      year={2024},
+      eprint={2409.16618},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2409.16618}, 
+}
+```
+
+Source Datasets:
 ```bibtex
 @inproceedings{nielsen2022mumin,
   title={MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset},
@@ -219,4 +235,5 @@ Note: This dataset is intended for academic and non-commercial use only, in comp
   year={2019},
   publisher={Kaggle},
   howpublished={\url{https://kaggle.com/competitions/nlp-getting-started}}
-}
+}
+```