Parsed spoken language in a 'Zoom' meeting with AWS-based sentiment analysis.

sample_transcript_sentiment_aws

## Format

A data frame with 30 rows of 17 variables:

batchMeetingId

a character meeting identification variable

utteranceId

an incremented numeric identifier for a marked speech utterance

'Zoom' display name attached to this speaker

utteranceStartSeconds

when the utterance started as the number of seconds from the start of the recording

utteranceStartTime

timestamp for the start of the utterance

utteranceEndSeconds

when the utterance ended as the number of seconds from the start of the recording

utteranceEndTime

timestamp for the end of the utterance

utteranceTimeWindow

duration of the utterance, in seconds

utteranceMessage

the text of the utterance

utteranceLanguage

language code of the utterance

userEmail

userId

numeric id of each speaker

aws_sentClass

character giving the sentiment classification of this text

aws_positive

probability that this text is mixed emotion

aws_negative

probability that this text is negative

aws_neutral

probability that this text is neutral

aws_mixed

probability that this text is positive

## Source

http://zoomgroupstats.org/