Signals API

term string

(Path Parameter - Required)
The query term

sources string or null

(Optional) Comma-separated data sources to generate results from.

Defaults to all sources.

Available sources: aylien, twitter, reddit, pinterest, tiktok, google, patents, weibo, instagram, pubmed, clinical_trials

geo string or null

(Optional) ISO-2 geo code specifying the country where results should be filtered from.

Defaults to null for global

check_cache string or null

(Optional) Boolean flag to indicate whether to use cached results or not.

Defaults to true.

x_term string

The query term

y_term string

Deprecated

geo string

The country the results are filtered for. (ISO-2 code)

is_sparse boolean

Describes the availability of data used to compute the signal. A true value means the system found limited data points to use.

inflection_markers list of strings

A list of dates indicating when inflection points occurred. Follows the format ‘YYYY-MM-DD’.

deflection_markers list of strings

A list of dates indicating when deflection points occurred. Follows the format ‘YYYY-MM-DD’.

rolling_avg list of lists

The unified signal that describes consumer interest of the trend. Represented as a time series that increments daily for up to 3 years. The nested arrays follow the format [“YYYY-MM-DD“, float], where the second element is a number in the range 0 to 100 and 100 is at point where the measured saturation for the trend is at its highest. Also known as the Impact Score

absolute_score list of lists

The absolute impact score represents the raw share of the volume of mentions and can be used to compare different trends based on the pure volume of conversation.

source_distribution dict

Describes the overall distribution of the volume of data used to computed the signal, where the sum of each source listed equals 100%

source_distribution.SOCIAL float

The percent volume of social data.

source_distribution.NEWS float

The percent volume of news data.

source_distribution.PATENTS float

The percent volume of patent data.

source_distribution.SEARCH float

The percent volume of search data.

social_distribution dict

Describes the overall distribution of the volume of data used to computed the SOCIAL part of the signal, where the sum of each source listed equals 100%

raw_count dict

Describes the count of retrieved documents for each of the listed data sources

growth_rate_max float

A score computed by finding percent change between first and last values in the signal.

growth_rate_3yr float

A score computed by finding percent change between the most recent signal score and the score 3yrs ago.

growth_rate_1yr float

A score computed by finding percent change between the most recent signal score and the score 1 year ago.

growth_rate_6m float

A score computed by finding percent change between the most recent signal score and the score 6 months ago.

growth_rate_3m float

A score computed by finding percent change between the most recent signal score and the score 3 months ago.

growth_rate_1m float

A score computed by finding percent change between the most recent signal score and the score 1 month ago.

growth_rate_2w float

A score computed by finding percent change between the most recent signal score and the score 2 weeks ago.

growth_rate_1w float

A score computed by finding percent change between the most recent signal score and the score 1 week ago.

polarity float

The most recent sentiment value. Can be in the range -1 and 1.

polarity_class enum

A label that describes the overall sentiment of online conversation. Cann be one of the possible values “POSITIVE” or “NEGATIVE”.

sentiment_score float

A numerical score that describes the overall sentiment score of conversation. Value is from 306 - 1534 (higher is more positive).

novelty_score float

A numerical score that describes how novel or well known the trend is. Value is from 306 - 1534 (higher is more novel).

past_score float

A numerical score that describes whether the trend occurred in the past or if it is predicted to gain greater interest in the future. Value is from 306 - 1534 (higher indicates higher interest).

packed_polarity list of lists

A time series that describes the sentiment, increments daily for up to 3 years. The nested arrays follow the format [“YYYY-MM-DD“, float], where the second element is a number in the range -1 to 1 and 1 means measured chatter was highly positive for the given day.

forecast list of dicts

(Deprecated)

12 month normalized forecast of the signal, incremented daily.

raw_forecast list of dicts

12 month forecast of the signal, incremented daily, based off the Impact Score (rolling_avg)

raw_forecast.date_key string

Follows the format ‘YYYY-MM-DD’

raw_forecast.saturation float

Predicted signal value. Relative to the signal values and unbounded to a range.

raw_forecast.min_conf_int_95 float

Lower bound 95% confidence interval

raw_forecast.max_conf_int_95 float

Upper bound 95% confidence interval

raw_forecast.min_conf_int_75 float

Lower bound 75% confidence interval

raw_forecast.max_conf_int_75 float

Upper bound 75% confidence interval

trend_norm

(Deprecated)

Same as rolling_avg

absolute_score_forecast

12 month forecast of the signal, incremented daily, based off absolute_score

future_score float

A numerical value that describes the slope of the forecast. Is a value in the range 306 - 1534 where higher means the trend is predicted to trend sharply upwards.

alert boolean

(BETA)

Is set to “true“ when the system identifies an inflection point in the past week, and would typically send an email alert to any user monitoring the trend.

leader enum

Describes where the source of the chatter has originated from and spread. Of the possible values “SEARCH“, “NEWS“, “SOCIAL“, or “PATENTS“.

days_lead integer

Given the leading indicator (leader attribute), describes by how many days the source carried the trend.

growth_label enum

A label that describes the historical direction of the trend over a 3 month period. Can be of the possibles values “growing“, “declining“, or “stationary“.

speed_label enum

The speed describes the rate of change in any direction over 3 months. An exponential trend represents a very sudden and steep slope, and an accelerating trend is a less steep slope. A stationary trend is one that has experienced no overall change. Can be of the possible values “stationary“, “accelerating“, or “exponential“.

volatility_label enum

A label that describes how chaotic or constant a trend a has been historically. Can be of the possible values “low“, “medium“, or “high“, where high means the trend has been very unstable.

growth_label_1m enum

A label that describes the historical direction of the trend over a 1 month period.

growth_label_3m enum

A label that describes the historical direction of the trend over a 3 month period

growth_label_6m enum

A label that describes the historical direction of the trend over a 6 month period.

growth_label_12m enum

A label that describes the historical direction of the trend over a 12 month period

growth_label_36m enum

A label that describes the historical direction of the trend over a 36 month period

speed_label_1m enum

The speed describes the rate of change in any direction over 1 month

speed_label_3m enum

The speed describes the rate of change in any direction over 3 months.

speed_label_6m enum

The speed describes the rate of change in any direction over 6 months.

speed_label_12m enum

The speed describes the rate of change in any direction over 12 months.

speed_label_36m enum

The speed describes the rate of change in any direction over 36 months.

volatility_label_1m enum

A label that describes how chaotic or constant a trend a has been historically over 1 month

volatility_label_3m enum

A label that describes how chaotic or constant a trend a has been historically over 3 months

volatility_label_6m enum

A label that describes how chaotic or constant a trend a has been historically over 6 months

volatility_label_12m enum

A label that describes how chaotic or constant a trend a has been historically over 12 months

volatility_label_36m enum

A label that describes how chaotic or constant a trend a has been historically over 36 months

data_sources array of strings

The set of data sources that have been used to construct the signal; and where there is sufficient data available. The list can include any of the values “social“, “news“, “patents“, or “search“.

distribution_label enum

A label that describes how concentrated or spread conversation is among different groups of voices. Can be of the values “concentrated“, or “distributed“, where concentrated means the topic is being disproportionately hyped up by a small number of individual voices, where as distributed means conversation is widely and evenly spread.

seasonality_label enum

Describes the presents of any cyclic trends such as yearly or month peaks. Can be of value “constant” or “seasonal“.

seasonality_types enum

Describes the classification of seasonality. Can be “Annual”, “Biannual”, “Quarterly”, or “Monthly”.

diversion_label enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment. A divergence score of none means there is no unusual momentum. Can be of the values “positive“, “none“, or “negative“.

diversion_label_1m enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment over 1 month

diversion_label_3m enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment over 3 months

diversion_label_6m enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment over 6 months

diversion_label_12m enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment over 12 months

diversion_label_36m enum

Deviation from the mean is an indicator that helps identify a sudden increase (or decrease) moment over 36 months

tone_label enum

Describes the overall tone surround the trend. Can be of the values “positive“, “neutral“, or “negative“.

tone_label_1m enum

Describes the overall tone surround the trend over 1 months

tone_label_3m enum

Describes the overall tone surround the trend over 3 months

tone_label_6m enum

Describes the overall tone surround the trend over 6 months

tone_label_12m enum

Describes the overall tone surround the trend over 12 months

tone_label_36m enum

Describes the overall tone surround the trend over 36 months

forecast_label enum

Relative to today, the saturation level of the trend's expected forecast over the next 12 months. Can be of the value “growing“, “declining“, or “stationary“.

forecast_label_1m enum

Relative to today, the saturation level of the trend's expected forecast over the next 1 months.

forecast_label_3m enum

Relative to today, the saturation level of the trend's expected forecast over the next 3 months.

forecast_label_6m enum

Relative to today, the saturation level of the trend's expected forecast over the next 6 months.

forecast_label_12m enum

Relative to today, the saturation level of the trend's expected forecast over the next 12 months.

forecast_label_max enum

Relative to today, the saturation level of the trend's expected forecast over the next 36 months.

novelty_label enum

A label that describes how novel or well known the trend is. Can be of the value “established“, or “novel“.

totem_future float

Describes the magnitude of the slope of the forecast on scale of 0 to 100.

totem_tone float

Describes the magnitude of the overall sentiment on scale of 0 to 100.

totem_speed float

Describes the magnitude of the rate of change on scale of 0 to 100.

forecast_abs_growth_3m float

The delta between first and last values in the forecasted signal over 3 months.

forecast_abs_growth_6m float

The delta between first and last values in the forecasted signal over 6 months.

forecast_abs_growth_12m float

The delta between first and last values in the forecasted signal over 12 months.

variable_importance array of hashes

Each hash contains a single variable (e.g. Novelty Label) and its importance , a float that represents the percentage importance of the variable in the analysis of historical impact.