Update README.md

README.md

@@ -97,34 +97,24 @@ The dataset is released as a single CSV file with 450 rows (one row per video) a
 
 [More Information Needed]
 
-#### Who are the source data producers?
+### Source Data Producers
+The source videos are publicly available content created by users of YouTube and Bilibili. The dataset release only includes annotations and metadata, not the raw video files, in compliance with the original platforms' terms of service.
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
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-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
+---
 
-Annotator Training: All annotators underwent a calibration phase using 20 pilot videos before formal annotation, with clear guidelines on temporal boundary marking, category labeling, and modality attribution
-Dual Annotation: Each video was independently annotated by two individuals, who identified harmful events, marked precise start/end timestamps, assigned category labels, identified contributing modalities, and wrote brief annotation rationales
-Disagreement Resolution: Disagreements regarding temporal boundaries, categories, or modalities were first addressed through discussion; unresolved cases were sent for a second round of review, with final labels determined by majority voting if consensus was not reached
-Quality Control: Inter-annotator agreement was measured on a randomly sampled subset, achieving a Cohen’s κ=0.74 for segment localization, with 92.3% agreement on category and modality labels
+### Annotations
 
+#### Annotation Process
+- **Annotator Training**: All annotators underwent a calibration phase using 20 pilot videos before formal annotation, with clear guidelines on temporal boundary marking, category labeling, and modality attribution.
+- **Dual Annotation**: Each video was independently annotated by two individuals, who identified harmful events, marked precise start/end timestamps, assigned category labels, identified contributing modalities, and wrote brief annotation rationales.
+- **Disagreement Resolution**: Disagreements regarding temporal boundaries, categories, or modalities were first addressed through discussion; unresolved cases were sent for a second round of review, with final labels determined by majority voting if consensus was not reached.
+- **Quality Control**: Inter-annotator agreement was measured on a randomly sampled subset, achieving a Cohen’s κ=0.74 for segment localization, with 92.3% agreement on category and modality labels.
 
 #### Who are the annotators?
-
 THVL-Bench was annotated by four experts with extensive experience in multimodal video analysis and content understanding. All annotators were informed of the potential risks prior to their participation and had unrestricted access to institutional psychological counseling resources throughout the annotation process.
 
 #### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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-[More Information Needed]
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+This dataset release does not contain any raw video files, personal identifiable information, or private sensitive data. Only anonymized video IDs, segment-level annotations, timestamps, and modality labels are included. All annotations are aggregated at the segment level with no reference to specific individuals in the videos. The dataset is intended for research purposes only, and all users are expected to comply with the original platforms' terms of service and use the data responsibly.
 ## Bias, Risks, and Limitations
 
 ### Limitations