*3.1.2.2. Retweets*

*3.1.1.2. Retweets*

the RStudio application.

*3.1.2.1. No-retweets*

*3.1.2. Kaci Fennell's placing in Miss Universe*

70 Machine Learning - Advanced Techniques and Emerging Applications

Among retweets for the topic, there were four hundred and fifty three (453) tweets were nega-

As depicted in **Figure 4** above, majority (2333) tweets of the three thousand two hundred and forty three (3243) tweets collected on Kaci Fennell's placing in the Miss Universe competition were negative. Upon examination of the tweets collected the negative tweets were expressions of anger and disappointment that Kaci did not win the Miss Universe competition or that she did not receive a higher placing than the fifth place ranking that she received. On the contrary, six hundred and five (605) tweets were classified as positive by

The graph above depicts the results obtained from analysis of tweets that were not retweeted, as in these tweets were posted by the original author. **Figure 5** shows that seven hundred and ninety (790) tweets were negative and three hundred and ninety nine (399) were positive.

tive and one thousand seven hundred and thirty eight (1438) were positive.

**Figure 4.** Sentiment polarity of tweets obtained on Kaci Fennell's placing in Miss Universe.

Among retweets for the topic, one thousand five hundred and thirty (1530) tweets were negative and two hundred and forty (240) were positive.
