**3.4. Riverton Landfill fire**

As depicted in **Figure 13**, the emotions discovered for the Riverton Landfill fire varied, more so than the other topical issues that was selected. The tweets analyzed resulted in emotions of anger, disgust, joy, sadness and surprise.

*3.4.1. No-retweets*

*3.4.2. Retweets*

*3.5.1. No-retweets*

more frequent emotions expressed.

**Figure 13.** Sentiment emotion of no-tweets obtained on the Riverton Landfill fire.

joy, sadness, disgust and anger.

**3.5. Barack Obama's visit to Jamaica**

Other emotions expressed were of joy and surprise.

Tweets posted by authors were of mixed emotions, with joy and sadness representing the

Using Sentiment Analysis and Machine Learning Algorithms to Determine Citizens' Perceptions

http://dx.doi.org/10.5772/intechopen.72521

77

The tweets that were retweeted by Twitter users on the Riverton Landfill fire were mostly of

As shown in **Figure 14**, there was difficulty in classifying the emotions associated with majority of the tweets. As a result of this, majority of the tweets for the Barack Obama's visit to Jamaica were classified as "unknown". Many factors including the use of the Jamaican creole and the use of sarcasm may have contributed to R's difficulty in determining the emotions of the tweets. This was noticed for the emotions depicted on the other topical issues selected.

Tweets posted by authors were of mixed emotions, varying from joy to surprise to fear.

**Figure 12.** Sentiment emotion of no-retweets obtained on the Kaci Fennell's placing in Miss Universe.

Using Sentiment Analysis and Machine Learning Algorithms to Determine Citizens' Perceptions http://dx.doi.org/10.5772/intechopen.72521 77

**Figure 13.** Sentiment emotion of no-tweets obtained on the Riverton Landfill fire.
