The top document-level sentiment analysis determines the tone of a document. It has data processing workflows that include traversing a text block to assess its tone – negative, positive, or neutral. Some tools also offer a third output called NULL, which means that the text is neither negative nor positive.
This sentiment analysis method works the best when all india whatsapp number the text being analyzed is lengthy.
While the top document-level sentiment analysis can offer the overall brand perception among the customer clusters, it cannot provide further actionable deeper insights.
For instance, take a look at the following reviews. These are commendable sentiment analysis examples:
Jack: I hate this brand…poorest customer service!
Brody: I don’t like their products.. such poor quality!!
While a top document-level sentiment analysis will show that both these statements are negative, it fails to identify the reasons behind these negative responses.
Hence, if you wish to assess the overall brand perception, you can opt for the top document-level analysis.
