Sentiment Analysis is generated through an advanced algorithm that calculates the sentiments of posts. This process identifies and categorizes the opinions expressed by users in online posts, determining whether their attitude toward a particular topic, product, or post is positive, negative, or neutral.
Sentiment Detection:
- The sentiment engine applies Crowd Intelligence’s own algorithms to detect the sentiment of a mention, including analysis of emojis and interactions, with an accuracy rate of 92%.
- Naturally, some texts are more challenging to analyze automatically, as the algorithm interprets sentiment based on context rather than just words.
- For example, even if the actual meaning of a text is positive—such as in a Vodafone ad that received high interaction—the sentiment engine might interpret it as negative if it combines keywords like “negative,” “not really appearing,” and “misrepresenting.”
- In such cases, you can manually label the statement by clicking on the icon that best represents the sentiment; the sentiment will then be updated accordingly.
Retweet Sentiment:
- The sentiment engine automatically labels passive engagements like retweets as negative.
- Crowd Intelligence recommends using the Mention Type filter to view the most accurate sentiment analysis.
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