Sentiment Analysis
Sentiment analysis is a technique that extracts and interprets emotions from text, identifying underlying sentiments such as positive, negative, or neutral. It combines elements of computer science, linguistics, and data analysis. Widely used in market research and customer feedback analysis, it helps uncover emotional subtext in language to provide insights into consumer attitudes and opinions.
Sentiment analysis is a natural language processing (NLP) technique used to categorize and interpret emotions, opinions, and attitudes conveyed in text. It classifies digital texts such as social media posts, product reviews, and news articles into predefined categories like positive, negative, or neutral, or more nuanced ones like joy, anger, or sadness.
This method provides valuable insights for businesses by analyzing customer opinions, aiding in a better understanding of consumer perceptions of products and services. For example:
"I absolutely love this product!" would be classified as positive.
"I'm really disappointed with this purchase." would be tagged as negative.
In broader contexts like social media and politics, sentiment analysis is vital for assessing public opinion and shaping strategies. It enhances digital interactions, allowing for personalized content recommendations and more empathetic responses.
A positive, negative, or neutral sentiment is identified for each transcript segment, and an overall sentiment of the entire transcript is also provided.
Sentiment can be toggled on and off. The setting will be saved till it is changed again.
FILTER
Users can select between agent sentiment, caller sentiment, and overall sentiment, with options: positive, neutral, and Negative.
Examples:
Agent sentiment is positive
The overall sentiment is negative
Caller sentiment is neutral
System Tags
System tags are the tags generated by the automatic processing of calls; these are different from user-generated tags.
Our platform processes the conversations and automatically tags them for key topics and intent during the call.
System Tags in Conversation details & Conversation scoring:
System tags are visible in blue color, while user tags are in grey. Clicking on a specific tag will take you to the timestamp in the transcription where the tag is detected. If the system tag is tagged on more than one timestamp, then you can use arrows to browse between the different timestamps.
You can hide the system tags from the transcription by simply turning off the “System tags” toggle
Filter & Search System tags:
System tags can be searched using filters on the Conversation, Conversation scoring pages, also a few reports, including Tags Summary, Call Logs, etc.
System tags in the Settings menu:
System tags can be accessed under Settings - Customization - Tags
Systems tags are labeled as (S), and they cannot be edited or deleted. Tags created by high-level groups that cannot be deleted will be labeled as Locked (L). 
You can sort tags alphabetically or by frequency. Tags can also be filtered by type (system or user).