Evidence map›Paper›PMID 39834549›Full record

ArticleFrontiers in genetics2024

Insights from social media into public perspectives on investigative genetic genealogy.

Sara Huston, Diana Madden, Andrea Villanes, Nathan Reed, Whitney Bash Brooks, Christopher Healey, Christi Guerrini

Abstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sara HustonMary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States.
Diana MaddenMary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States.
Andrea VillanesDepartment of Computer Science, Institute for Advanced Analytics, North Carolina State University, Raleigh, NC, United States.
Nathan ReedMary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States.
Whitney Bash BrooksBaylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, TX, United States.
Christopher HealeyDepartment of Computer Science, Institute for Advanced Analytics, North Carolina State University, Raleigh, NC, United States.
Christi GuerriniBaylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, TX, United States.

Funding

IGG on the Internet: Characterizing Public Perspectives on Law Enforcement Use of Genetic Genealogy Data in Social MediaR01HG011268 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GUERRINI, CHRISTI, MCGUIRE, AMY L · 2020 to 2023
$2.4M
NHGRI NIH HHS R01 HG011268
6 · The paper itself

Abstract

Social media sites like X (formerly Twitter) increasingly serve as spaces for the public to discuss controversial topics. Social media can spark extreme viewpoints and spread biased or inaccurate information while simultaneously allowing for debate around policy-relevant topics. The arrest of Joseph J. DeAngelo in April 2018 ignited a barrage of social media conversations on how DNA and genetic genealogy led to the suspect. These conversations continued over the following years as policies changed and as the use of the approach expanded. We examined social media coverage of investigative genetic genealogy (IGG) to characterize the volume and temporal patterns in the topics and sentiments of these public conversations. First, using a data analytics tool Brandwatch Consumer Research, we built flexible search strings to collect tweets from the social media platform Twitter/X for IGG-relevant content published from 2018 to 2022, resulting in 24,209 tweets. Second, we applied informatics tools to the dataset to generate topic clusters and analyze trends in cluster volume and distribution over time to define the top 25 peaks in tweet volume, representing the 25 events that generated the highest volume of conversation over the 5-year period. Third, drawing on the contextual framework of key IGG events, we selected three of the top ten events to code for sentiment along with a randomly sampled subset of tweets across the timeframe. Qualitative coding for position on IGG revealed a majority of tweets were supportive of the use of IGG, but key concerns were also voiced about the ethics of IGG. Over a third of conversations on Twitter/X were on either cases solved or suggestions for use of IGG. We archived the social media data for future research. These data highlight key areas of public support and concern within IGG processes and across application contexts.

Indexed as

DNA testingforensic DNAinvestigative genetic genealogykinship analysispublic understanding of sciencesocial media

Identifiers

PMID39834549
PMCPMC11743634

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.