How is the mood calculated or rated

Sentiment analysis

In sentiment analysis, the Basic mood the Fans or Subscribers to a post in the form of a Like-Dislike-Ratio about a longer period calculated. As absolute size will the number the different Comments reproduced to a post and a positive or negative Mood calculated.1

The content of the comments (criticism, praise, suggestions for improvement) can be evaluated with a sentiment analysis.2

The sentiment is the expression of the basic mood of the fans / followers / subscribers for a post. This is divided into positive, neutral and negative basic mood. In order to be able to represent a sentiment, a interaction in the form of Comments have taken place. As an absolute value, the sentiment reflects the number of different comments on a post. This makes it possible to see at a glance whether a positive or negative prevailing mood prevails.3

In the sentiment analysis, depending on the design of the analysis, whole texts or single terms according to her tonality divided up. The possible approaches can be divided into two types. On the one hand, methods of the monitored machine learning a classification model is trained, which is able to automatically convert texts into positive, negative and neutral text classify. On the other hand, so-called. Lexicon-based procedures used. The methods evaluate the tonality in texts according to how often they contain certain words from the available lists of positive and negative words.4

Sentiment Analysis:

positive: Brilliant effort guys / Loved your work.
: Good job, but I will except a lot more in the future.
: Totally dissatisfied with this service. Worst customer care ever.

The influencer marketing agency style ranking offers sentiment analyzes as part of the evaluation in the context of influencer marketing campaigns.

Individual evidence

  • 1 Deges, Frank (2018): Quick Guide Influencer Marketing, 1st edition, Brühl, Germany, Springer Gabler, p.123
  • 2 Deges, Frank (2018): Quick Guide Influencer Marketing, 1st edition, Brühl, Germany, Springer Gabler, p. 80
  • 3 Deges, Frank (2018): Quick Guide Influencer Marketing, 1st edition, Brühl, Germany, Springer Gabler, p.123
  • 4 Meffert, Heribert / Burmann, Christoph / Kirchgeorg, Manfred / Eisenbeiß, Maik (2019): Marketing, 13th edition, Münster, Bremen, Leipzig, Germany, Springer Gabler, p. 209

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style ranking has the Macromedia University in Cologne with the analysis current practical topics in influencer marketing instructed. These definition finds its origin in the Analysis and definition of the university project. Numerous definitions were compared and the chosen above than those under scientific criteria most relevant selected.

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