During the last few elections that occurred in the past decade, many polls are struggling to correctly predict election results, such instances could be seen in 2016’s U.S. presidential election and the Brexit referendum in UK. These wrong predictions are forcing researchers to explore more effective methods, like big data analytics, to better understand public opinion. This study presents the potential of some big data analytics tools like Google Trends to forecast upcoming 2024 U.S. presidential elections, highlighting their ability to capture more authentic public sentiments compared to traditional polls, which often suffer from social desirability bias. By looking at search patterns related to racial animus, immigration skepticism, and far-right sentiment, the research inspects how these factors have influenced voter behavior in the 2008, 2012, and 2016 elections. It also explores how integrating Google search data with other tools like Google Keyword Planner and traditional polling can enhance predictions for the 2024 election. Ultimately, the research suggests that combining these approaches can provide deeper insights into voter attitudes, offering a more accurate tool for predicting election results.

Big Data Analytics U.S. Presidential Elections Google Trends Analysis Political Analysis