Demo Data from SIGIR 2026 / reviewers in the wild / expert
Hamest Tamrazyan
dblp:353/2177
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2026
0000-0001-9630-0195ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% | |
| Artificial intelligence
1 paper |
Information extraction and text analysis · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational social science and digital humanities › cultural heritage
cultural heritage analysis |
1.0 | 1 | 2026 | A Dataset of Cultural Heritage Manipulation on English Wikipedia in the Russo-Ukrainian Context · SIGIR 2026 |
Methods — techniques the papers use, named apart from their topics
dataset construction · 3.0annotation · 3.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | A Dataset of Cultural Heritage Manipulation on English Wikipedia in the Russo-Ukrainian ContextabstractDigital knowledge platforms increasingly shape how cultural heritage and historical responsibility are represented and remembered, yet they are vulnerable to subtle forms of narrative manipulation that rarely appear as explicit misinformation. We present a new dataset of English Wikipedia revision pairs designed to support the systematic study of cultural heritage manipulation in the context of the Russo--Ukrainian conflict. The resource captures fine-grained textual changes through which cultural attribution, agency, and legitimacy are incrementally reframed within a collaborative encyclopedic infrastructure. By providing paired revisions, editorial context, and consistent annotations, the dataset enables analysis of discursive interventions that remain procedurally legitimate while producing cumulative cultural effects. The dataset is released to support research in information retrieval, natural language processing, and computational social science on detecting and understanding subtle narrative change in large-scale, collaborative knowledge systems. The resource is available at https://zenodo.org/records/19883068. Maxime Garambois, Hamest Tamrazyan, Emanuela Boros |
SIGIR | 2 |
| 2024 | Developing a Standardised Vocabulary for Ukrainian Epigraphy and Expanding Digital Epigraphic Resources
Hamest Tamrazyan, Emanuela Boros, Frédéric Kaplan |
TPDL (2) | 1 |