Dedan Kimathi University of Technology (DeKUT) is a Chartered Public University that has two campuses: the Main Campus in Nyeri and Nairobi Campus along Loita street.

Over the past 20 years, Kenya's demand for petroleum products has proliferated. This is mainly because this particular commodity is used in many sectors of the country's economy. Exchange rates are impacted by constantly shifting prices, which also impact Kenya's industrial output of commodities. The cost of other items produced and even the expansion of the economy is significantly impacted by any change in the price of petroleum products. Therefore, accurate petroleum price forecasting is critical for devising policies that are suitable to curb fuel-related shocks. Data mining techniques are the tools used to find valuable patterns in data. Data mining techniques used in petroleum price prediction, including artificial neural networks (ANNs), support vector machines (SVMs), and intelligent optimization techniques like the genetic algorithm (GA), have grown increasingly popular. This study provides a comprehensive review of the existing data mining techniques for making predictions on petroleum prices. The data mining techniques are classified into regression models, deep neural network models, fuzzy sets and logic, and hybrid models. A detailed discussion of how these models are developed and the accuracy of the models is provided.

In this new era of social media, social networks are becoming increasingly important sources of user-generated content on the internet. These kinds of information resources, which include a lot of people's feelings, opinions, feedback, and reviews, are very useful for big businesses, markets, politics, journalism, and many other fields. Politics is one of the most talked-about and popular topics on social media networks right now. Many politicians use micro-blogging services like Twitter because they have a large number of followers and supporters on those networks. Politicians, political parties, political organizations, and foundations use social media networks to communicate with citizens ahead of time. Today, social media is used by hundreds of thousands of political groups and politicians. On these social media networks, every politician and political party has millions of followers, and politicians find new and innovative ways to urge individuals to participate in politics. Furthermore, social media assists politicians in various decision-making processes by providing recommendations, such as developing policies and strategies based on previous experiences, recommending and selecting suitable candidates for a particular constituency, recommending a suitable person for a particular position in the party, and launching a political campaign based on citizen sentiments on various issues and controversies, among other things. This research is a review on the use of social network analysis (SNA) and semantic analysis (SA) on the Twitter platform to study the supporters networks of political leaders because it can help in decision-making when predicting their political futures.