ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2009
Perplexity analysis of obesity news coverage.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- N-gram analysis of 970 microbial organisms reveals presence of biological language models.BMC bioinformatics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
An important task performed during the analysis of health news coverage is the identification of news articles that are related to a specific health topic (e.g. obesity). This is often done using a combination of keyword searching and manual encoding of news content. Statistical language models and their evaluation metric, perplexity, may help to automate this task. A perplexity study of obesity news was performed to evaluate perplexity as a measure of the similarity of news corpora to obesity news content. The results of this study showed that perplexity increased as news coverage became more general relative to obesity news (obesity news approximately 187, general health news approximately 278, general news approximately 378, general news across multiple publishers approximately 382). This indicates that language model perplexity can measure the similarity news content to obesity news coverage, and could be used as the basis for an automated health news classifier.
Indexed as
Identifiers
20351893PMC2815490What OpenQuestion holds
Registered trials
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.