On Detecting Cherry-picked Trendlines
Summary: Introduces a support metric to quantify how cherry-picked temporal trendlines and their associated claims are. Develops efficient algorithms for scoring and discovering maximally supported statements, with theoretical guarantees and empirical validation. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Abolfazl Asudeh (University of Illinois Chicago)
- 2. H. V. Jagadish (University of Michigan)
- 3. You (Will) Wu (Google)
- 4. Cong Yu (Google)
BibTeX Citation
@article{asudeh_vldb20,
title = {{On Detecting Cherry-picked Trendlines}},
author = {Asudeh, Abolfazl and Jagadish, H. V. and Wu, You (Will) and Yu, Cong},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {6},
pages = {939--952},
doi = {10.14778/3380750.3380762},
url = {https://doi.org/10.14778/3380750.3380762},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,962 | Fairly Evaluating and Scoring Items in a Data Set | 2020 | VLDB | 5.6330612e-05 |
| 8,355 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 5.3482186e-05 |
| 9,579 | On Detecting Cherry-picked Generalizations | 2022 | VLDB | 5.1571823e-05 |
| 10,618 | Analyzing Deviations from Monotonic Trends through Database Repair | 2026 | SIGMOD | 4.9793485e-05 |
| 11,362 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.9793485e-05 |
| 11,400 | ClaimIt: Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.9793485e-05 |
| 11,899 | OREO: Detection of Cherry-picked Generalizations | 2022 | VLDB | 4.9793485e-05 |
| 11,970 | To Intervene or Not To Intervene: Cost based Intervention for Combating Fake News | 2021 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,379 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.0001086418 |
| 2,482 | ClaimBuster: The First-ever End-to-end Fact-checking System | 2017 | VLDB | 8.399913e-05 |
| 2,645 | Progressive Approach to Relational Entity Resolution | 2014 | VLDB | 8.177221e-05 |
| 3,178 | Toward Computational Fact-Checking | 2014 | VLDB | 7.5655186e-05 |
| 3,552 | Knowledge-Based Trust: Estimating the Trustworthiness of Web Sources | 2015 | VLDB | 7.2097862e-05 |
| 5,610 | On Obtaining Stable Rankings | 2019 | VLDB | 6.0686149e-05 |
| 5,961 | DaNaLIX: a Domain-adaptive Natural Language Interface for Querying XML | 2007 | SIGMOD | 5.9332159e-05 |
| 7,060 | Data In, Fact Out: Automated Monitoring of Facts by FactWatcher | 2014 | VLDB | 5.6103442e-05 |
| 9,091 | MithraRanking: A System for Responsible Ranking Design | 2019 | SIGMOD | 5.2283159e-05 |
| 9,187 | Finding Diverse, High-Value Representatives on a Surface of Answers | 2017 | VLDB | 5.211358e-05 |
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|---|---|---|---|---|
| 1 | 915 | Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures | 2008 | VLDB |
| 2 | 3,323 | A Confidence-Aware Approach for Truth Discovery on Long-Tail Data | 2015 | VLDB |
| 3 | 11,899 | OREO: Detection of Cherry-picked Generalizations | 2022 | VLDB |
| 4 | 3,702 | Identifying Representative Trends in Massive Time Series Data Sets Using Sketches | 2000 | VLDB |
| 5 | 6,268 | An Experimental Evaluation of Anomaly Detection in Time Series | 2024 | VLDB |
| 6 | 12,462 | iCheck: Computationally Combating "Lies, D-ned Lies, and Statistics" | 2014 | SIGMOD |
| 7 | 3,178 | Toward Computational Fact-Checking | 2014 | VLDB |
| 8 | 8,382 | Mining Deviants in a Time Series Database | 1999 | VLDB |
| 9 | 11,362 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB |
| 10 | 9,579 | On Detecting Cherry-picked Generalizations | 2022 | VLDB |