DOI: 10.5281/zenodo.18203015
title: Dataset: Antisemitism and Views of Israel on X (Twitter) and TikTok: Annotations from the October 2025 Hostage Release

description: This dataset contains annotations of social media posts from X (Twitter) and TikTok collected around the October 13, 2025 release of the last living hostages taken during the October 7, 2023 Hamas attack on Israel. The dataset was compiled as part of the class "Israel on Social Media" at Indiana University.

Content:

The dataset contains 340 social media posts (189 from X, 151 from TikTok) collected across three time periods using the search term "Israel": about two weeks before October 13, 2025 (baseline period); October 13, 2025 (day of the hostage release); and about two weeks after October 13, 2025 (aftermath period). Posts were retrieved from fresh accounts without browsing history to capture content as it would appear to new users.

The distribution of posts by platform and time period is as follows:






Platform
Pre-Oct 13
Oct 13
Post-Oct 13
Total




X (Twitter)
65
58
66
189


TikTok
42
38
71
151





Note: Some posts appeared in multiple time periods. 

Annotation:

Each post was annotated by multiple coders (18–19 annotators for X samples, 10–11 annotators for TikTok samples) on the following dimensions:



Views of Israel (5-point scale: 1=Very Negative to 5=Very Positive)

Antisemitism according to the IHRA definition (5-point scale: Certainly not, Probably not, Don't know, Probably yes, Certainly yes)

IHRA Section (which specific provision of the IHRA working definition applies, if any)

Themes (e.g., Hostages, Ceasefire, Destruction in Gaza, Hamas, Israel/Jewish pride)

Conspiracy theories (specific types)

Calling out antisemitism (whether the post critiques rather than expresses antisemitism)


File Description:

The dataset is provided in wide format (.xlsx), with each row representing a single post. Columns include:



Platform: X or TikTok

Time_Period: Pre-Oct 13, Oct 13, or Post-Oct 13

Sample_ID: Identifier for the sample batch

Sample_Name: Name of the sample

Sr_Number: Post number within sample

Object_ID: Unique identifier for the post

Annotator_[1-19]_Views_of_Israel: Each annotator's rating of views toward Israel

Annotator_[1-19]_Is_Antisemitic_IHRA: Each annotator's assessment of antisemitism

Annotator_[1-19]_IHRA_Section: IHRA provisions identified by each annotator

Annotator_[1-19]_Calling_out_Antisemitism: Whether post calls out antisemitism

Annotator_[1-19]_Includes_Conspiracy: Conspiracy theory content identified

Annotator_[1-19]_Themes: Themes identified by each annotator

Annotator_[1-19]_Comments: Annotator comments

Annotator_[1-19]_Time_Taken: Time spent on annotation (seconds)


 

Acknowledgements:

We are grateful for the contributions and annotations of all students in the "Israel on Social Media" class at Indiana University in Fall 2025. We used Indiana University's Social Media Annotation Portal (https://annotate.osome.iu.edu/) for the annotation (Jikeli, Soemer, & Karali, 2024).

References:

Jikeli, G., Soemer, K., & Karali, S. (2024). Annotating live messages on social media: Testing the efficiency of the AnnotHate – live data annotation portal. Journal of Computational Social Science, 7, 571–585.