NetBase

The table below gives information about all the data fields that you can import from NetBase.

The fields that you can fetch in Adverity are updated regularly to reflect updates to data source APIs. As a result, the fields shown here may not be the same as the fields available in Adverity. If you notice a difference between this documentation and the fields you see in Adverity, please contact your Adverity account manager for more information.

To see the fields you can collect from another data source, go back to the Available fields in Adverity overview.

Field UI name

Field API name

Description

Use in Adverity

Docs

authors

Returns the approximate number of unique users who authored mentions matching the topic

metric

comments

Returns the number of comments/replies for matching sound bites. This metric is supported for Facebook- Twitter Firehose- Instagram (published after August 1- 2017)- and YouTube (published after December 5- 2017).

metric

dislikes

Returns the number of dislikes for matching YouTube posts published after December 5- 2017.

metric

likes

Returns the number of likes for matching sound bites. This metric is supported for Facebook- Twitter Firehose- Instagram (published after August 1- 2017)- and YouTube (published after December 5- 2017).

metric

mentions

Returns the total number of matching sound bites.

metric

negatives

Returns the number of matching sound bites containing negative sentiment.

metric

net_sentiment

Returns the topic's net sentiment score- which expresses the ratio of positive to negative sentiment about a brand. The net sentiment formula is: ( ( Positives – Negatives) / ( Positives + Negatives ) ) * 100.

metric

neutrals

Returns the number of matching sound bites containing no sentiment.

metric

original_posts

Returns the number of matching original posts.

metric

passion_intensity

Returns the topic's passion intensity score- which expresses the ratio of strong emotions (such as “love” or “hate”) to all emotions expressed about a brand. The passion intensity formulas is: A * (Strong Emotions – Weak Emotions) / ( Strong Emotions + Weak Emotions ) + B. You can use the following two parameter values to retrieve the number of strong and weak emotions used in the formula.

metric

positives

Returns the number of matching sound bites containing positive sentiment.

metric

posts

Returns the total number of matching documents.

metric

potential_impressions

Returns the estimated number of people who might have viewed an author’s posts.

metric

reblogs/retweets

Returns the number of matching shares/reblogs/Retweets.

metric

replies

Returns the number of matching replies/comments.

metric

shares/retweets

Returns the number of matching shares/reblogs/Retweets (supported for Facebook and Twitter Firehose data).

metric

strong_emotions

Returns the number of matching sound bites containing strong emotions.

metric

topic_id

ID of the topic.

dimension

topic_name

Name of the topic.

dimension

total_engagements

Returns the number of matching shares/reblogs/Retweets (supported for Facebook and Twitter Firehose data).

metric

total_engagements_per_post

Returns the average number of engagements on original posts matching the analysis using the formula Total Engagements on Original Posts / Number of Original Posts. This metric is supported for Facebook- Twitter Firehose- Instagram (published after August 1- 2017)- and YouTube (published after December 5- 2017.

metric

views

Returns the number of views for matching YouTube posts published after December 5- 2017.

metric

weak_emotions

Returns the number of matching sound bites containing weak emotions.

metric