Sentence examples for sentiment mapping from inspiring English sources

Sentiment mapping adds location to sentiment analysis.

Are transport providers now turning to sentiment mapping to improve their services?

One of the greatest ambitions for sentiment mapping is to break down the antagonism between transport providers and the public; to redefine that relationship as aspirational and constructive, and for mutual benefit.

This is where sentiment analysis and sentiment mapping come in, a concept being explored by the Royal College of Art, startup Commonplace and the UK's technology and innovation centre, Transport Systems Catapult.

"Sentiment mapping" of all this social data is giving valuable feedback to transport operators, says Mike Saunders, chief executive of Commonplace, a firm specialising in the art.

The centre is also experimenting with so-called sentiment mapping, gathering the tweets and other social media interactions related to the eight major rail operators which serve London and representing them as coloured blocks on a map - with each colour representing a different mood, aiming to show how customers rate each train company on a daily basis.

In response to a question from a reporter, John Bohannon of Science, to identify the highest and lowest sentiment locations in Manhattan, I personally looked at the sentiment map and found the highest sentiment spot to be an area of the Fort Tryon Park, and a single data area of low sentiment that overlapped with the location of the Hunter College High School.

Researchers used the program to classify the over 600,000 geographically tagged messages they recorded citywide during a two-week period in April 2012 – two school years ago, students pointed out — to create a "sentiment map of New York City" along with the study, which was published in August.

Among the upcoming features are the addition of other datasets for sentiment analysis, maps to place the online activity and conversations in geographic context, and support for mobile devices.

In sentiment analysis, Leximancer maps the frequency and co-occurrence of concepts with an in-built thesaurus of sentiment terms (negative versus positive).

The software package Leximancer [ 65], originally created at the University of Queensland in Australia, includes two key functions concept mapping and sentiment analysis that are fairly standard in the field.