Areas of expertise: NLP, ML, ML Experimentation, Labeling, Data Science, Fraud
Public
Edited
Jan 3, 2023
chartData.get("united_coverage", 0)
coverage_score = _.round(
chartDataMeasurements.get("Average Headline Bias", 0),
3
)
topic_bias = {
let coverage_score = _.round(
chartDataMeasurements.get("Average Headline Bias", 0),
3
);
let coverage = "Low Subjectivity";
if (coverage_score > 0.6) {
coverage = "High Subjectivity";
} else if (tcoverage_score > 0.2) {
coverage = "Medium Subjectivity";
} else {
coverage = "Low Subjectivity";
}
return coverage;
}
top_15_topics = dt
.groupby("topic_name")
.rollup({ attention_sum: (d) => op.sum(d.attention_score) })
.orderby(aq.desc("attention_sum"))
.slice(0, 15)
.select("topic_name")
top_10_topic_source_bias_attention = aq
.from(
dt
.objects()
.filter((o) => top_10_topics.array("topic_name").includes(o.topic_name))
)
.groupby("topic_name", "source_bias", "source_bias_readable")
.params({ division_factor: division_factor })
.rollup({
attention_sum: (d, $) => op.sum(d.attention_score) / $.division_factor
})
skewed_topics_with_attention_source.view()
source_divergence.view()
mean_divergence = source_divergence
.rollup({ mean: (d) => op.mean(d.divergence) })
.values("mean")
function getMaxDate(dates) {
let maxDate = dates[0];
for (let i = 1; i < dates.length; i++) {
if (dates[i] > maxDate) {
maxDate = dates[i];
}
}
return maxDate;
}
function formatDate(dateString) {
const date = new Date(dateString);
const options = { year: "numeric", month: "short", day: "numeric" };
return date.toLocaleDateString("en-US", options);
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
