NetBase
The table below gives information about all the data fields that you can import from NetBase.
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 |
Data Type |
Description |
Use in Adverity |
Docs |
|---|---|---|---|---|---|
|
|
authors |
long |
Returns the approximate number of unique users who authored mentions matching the topic |
metric |
|
|
|
comments |
long |
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 |
long |
Returns the number of dislikes for matching YouTube posts published after December 5- 2017. |
metric |
|
|
|
likes |
long |
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 |
long |
Returns the total number of matching sound bites. |
metric |
|
|
|
negatives |
long |
Returns the number of matching sound bites containing negative sentiment. |
metric |
|
|
|
net_sentiment |
float |
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 |
long |
Returns the number of matching sound bites containing no sentiment. |
metric |
|
|
|
original_posts |
long |
Returns the number of matching original posts. |
metric |
|
|
|
passion_intensity |
float |
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 |
long |
Returns the number of matching sound bites containing positive sentiment. |
metric |
|
|
|
posts |
long |
Returns the total number of matching documents. |
metric |
|
|
|
potential_impressions |
long |
Returns the estimated number of people who might have viewed an author’s posts. |
metric |
|
|
|
reblogs/retweets |
long |
Returns the number of matching shares/reblogs/Retweets. |
metric |
|
|
|
replies |
long |
Returns the number of matching replies/comments. |
metric |
|
|
|
shares/retweets |
long |
Returns the number of matching shares/reblogs/Retweets (supported for Facebook and Twitter Firehose data). |
metric |
|
|
|
strong_emotions |
long |
Returns the number of matching sound bites containing strong emotions. |
metric |
|
|
|
topic_id |
string |
ID of the topic. |
dimension |
|
|
|
topic_name |
string |
Name of the topic. |
dimension |
|
|
|
total_engagements |
long |
Returns the number of matching shares/reblogs/Retweets (supported for Facebook and Twitter Firehose data). |
metric |
|
|
|
total_engagements_per_post |
float |
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 |
long |
Returns the number of views for matching YouTube posts published after December 5- 2017. |
metric |
|
|
|
weak_emotions |
long |
Returns the number of matching sound bites containing weak emotions. |
metric |
|