SentimentScores (hyperlocal datastream)
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Verified Data Provider| # | start_time |
finish_time |
area_id |
geom |
km2 |
population |
sample_size |
sentiment_negative |
sentiment_neutral |
sentiment_positive |
sentiment_trust |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx |
| 2 | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx |
| 3 | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx |
| 4 | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx |
| 5 | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx |
| 6 | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx |
| 7 | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx |
| 8 | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx |
| 9 | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx |
| 10 | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx |
| ... | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
start_time
|
String | 2022-08-01 00:00:00+00 | |
|
finish_time
|
String | 2022-08-08 00:00:00+00 | |
|
area_id
|
String | 006464db-d97a-d07f-5d96-001cd1968ae3 | |
|
geom
|
String | {"type":"MultiPolygon","coordinates":[[[[-75.687078817,45... | |
|
km2
|
Float | 0.0468 | |
|
population
|
Integer | 606 | |
|
sample_size
|
Integer | 372 | |
|
sentiment_negative
|
Integer | 60 | |
|
sentiment_neutral
|
Integer | 15 | |
|
sentiment_positive
|
Integer | 25 | |
|
sentiment_trust
|
Integer | 80 |
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
time_start
|
DateTime | 2023-01-01 00:00:00+00 | |
|
time_finish
|
DateTime | 2023-02 00:00:00+00 | |
|
area_id
|
String | bcd7fddb-0d23-d8e6-0757-5c5cdbbdc42e | |
|
geom
|
Text | {"type":"MultiPolygon","coordinates":[[[[-79.39505368,43.... | |
|
area_km2
|
Float | 2.34222083538226 | |
|
population
|
Integer | 38452 | |
|
sentiment_negative
|
Float | 0.03 | |
|
sentiment_neutral
|
Float | 0.62 | |
|
sentiment_positive
|
Float | 0.40 | |
|
sentiment_volume
|
Integer | 564 | |
|
sentiment_trust
|
Float | 0.91 |
Description
Geography
History
Volume
| 480,000 | block polygons |
| 365 | days |
Pricing
| License | Starts at |
|---|---|
| One-off purchase | Available |
| Monthly License | Available |
| Yearly License | Available |
| Usage-based | Available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Products
Frequently asked questions
What is SentimentScores (hyperlocal datastream)?
Capture the overall breakdown of positive, neutral & negative vibe of any community at any point in time. Measurable at city, postal, neighborhood or block precision over monthly, weekly or daily time periods.
What is SentimentScores (hyperlocal datastream) used for?
This product has 5 key use cases. Affectra recommends using the data for Location Intelligence, Demographic Segmentation, Benchmarking, Retail Site Selection, and Local Economic Forecasting. Global businesses and organizations buy AI & ML Training Data from Affectra to fuel their analytics and enrichment.
Who can use SentimentScores (hyperlocal datastream)?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for AI & ML Training Data. Get in touch with Affectra to see what their data can do for your business and find out which integrations they provide.
How far back does the data in SentimentScores (hyperlocal datastream) go?
This Tabular Data has 2 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, yearly, and on-demand basis.
Which countries does SentimentScores (hyperlocal datastream) cover?
This product includes data covering 1 country like Canada. Affectra is headquartered in Canada.
How much does SentimentScores (hyperlocal datastream) cost?
Pricing information for SentimentScores (hyperlocal datastream) is available by getting in contact with Affectra. Connect with Affectra to get a quote and arrange custom pricing models based on your data requirements.
How can I get SentimentScores (hyperlocal datastream)?
Businesses can buy AI & ML Training Data from Affectra and get the data via S3 Bucket and Email. Depending on your data requirements and subscription budget, Affectra can deliver this product in .json and .csv format.
What is the data quality of SentimentScores (hyperlocal datastream)?
Affectra has reported that this product has the following quality and accuracy assurances: 100% geo-coverage, 83% avg accuracy. You can compare and assess the data quality of Affectra using Datarade’s data marketplace.
What are similar products to SentimentScores (hyperlocal datastream)?
This Tabular Data has 3 related products. These alternatives include The Data Appeal Global Location Data Insights, Consumer Sentiment Data, Map Data, Sentiment API, Dataset 251M POI Data Coverage from 2019, TrendingTopics (hyperlocal datastream), and Factori People Data Global coverage with 900 Million+ device profiles. You can compare the best AI & ML Training Data providers and products via Datarade’s data marketplace and get the right data for your use case.
Affectra
capture the local vibe of any place at any time
Verified Provider