The Sentiment Analysis widget reveals the most positive and negative tweets. Up to 100 of the most positive and negative tweets are visualized in the graph and listed in their respective columns.

The Graph

The Pie Chart in the top left part of the graph reveals the overall sentiment breakdown for the selected time period for all tweets. Hover over the two pie slices to get the percentages.
The Bubbles in the graph represents the most significant individual tweets from the time period. The further up on the X-axis the more positive the tweets, the further down on the X-axis the more negative. The size of the bubble indicates the level of engagement – the larger the bubble the more retweets. Select a bubble to see that tweet in the respective columns below.

The Algorithm

The sentiment analysis provided is powered by a natural language processing (NLP) algorithm optimized for healthcare and is proprietary to Symplur. This algorithm extracts subjective information from healthcare conversations in order to determine polarity about healthcare issues. The method used for determining sentiment employs a scaling system for three classes of neutral, positive and negative sentiment. The algorithm also interprets text-based emoticons like “:)” as a sentiment signal.

Filters

  • Filter the Healthcare Stakeholders voices by toggling each stakeholder in the toolbar. This filters both the bubbles in the graph and the columns. It will also update the Pie Chart with the average sentiment breakdown of the remaining filtered tweets.

Engagements

  • Select and Drag in the bubble graph to zoom in on a more narrow time period. 
  • Click a Bubble to see that tweet in the respective columns below.
  • Toggle the Lock Switch or Click a Column to enable/disable scrolling inside a column.
  • Click the Tweet Timestamp to open the specific tweet on Twitter.
  • Click Twitter Handle link to reveal full profile and options to see this user's own tweets, received mentions and it's Healthcare Social Graph page
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