Analysis of public awareness on global warming: Forecasting using Google Trends and FB prophet

Global warming is a world problem that must be solved jointly by all countries in the world. Public awareness of global warming shows a decreasing trend over time, as shown in the global community's search results for the keyword global warming which tends to decrease in number. So, research must be carried out to find out the causes of the decline in global public awareness of this issue. This research aims to predict several keywords related to global warming and try to find the reasons why world public awareness tends to continue to decline. This research uses Google Trends to retrieve the dataset and uses the FB prophet model as a forecasting algorithm in machine learning. The research results show that the trend in people's searches for the keyword "global warming" will tend to decline over the next year. Another finding is that there are contradictory keywords on Google Trends that tend to increase, namely "evidence of global warming" and "why climate change is fake". The MAPE (Mean Average Percentage Error) score for the two contradictory keywords is 0.16 and 0.15. Another finding is, if the search dataset on Google Trends has a high fluctuating number of searches, additional columns can be added to the dataset by using the max function to combine several related keywords to retrieve the highest number of searches. Added max column can increase MAPE score in forecasting results. The MAPE score in the max column is 0.159. Another finding was that contradictory keywords on Google Trends came from South Africa, America, Australia, the Philippines, England, Canada, Vietnam, and India.