Big Data Text Analysis

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Sentiment Searching and Comparisons

Mozdeh estimates the strength of positive and negative sentiment in each text. This can be used to filter the search results by sentiment or identify terms that occur more frequently in a particular sentiment range. Sentiment is measured on a scale of 1 (no positive sentiment) to 5 (very strong positive sentiment) and -1 (no negative sentiment) to 5 (very strong negative sentiment).

    1. Download Mozdeh, collect data and open the project with the data.
    2. To find words that are more common in positive texts, leave the search box blank and click the + button in the sentiment section (or minus for negative tweets). This sets the positive sentiment minimum to be 3 (at least moderate positive sentiment) and the negative maximum to be 2 (at most mild negative sentiment). Then click Search. [see below right]
    3. For a list of terms that associate with the selected sentiment range (i.e., occur more often in texts within the specified range than in other texts), click the Calculate word frequencies for all search matches button. The results below are for negative texts and the most valuable terms are the ones describing a topic rather than a sentiment.

    4. This can be combined with gender or keywords - for example, the setting below is for positive tweets from males, for a collection of negative tweets (giving the results above).



Made by the Statistical Cybermetrics Research Group at the University of Wolverhampton during the CREEN and CyberEmotions EU projects.