Poll AI Charts and Graphs
What role can charts and tables play in the world of politics and even issue-oriented campaigns?
I read polls and am often fascinated by those colorful images that capsulize important data points. As a result, I decided to talk to my artificial intelligence buddy, who I dub PoliAI to help me comprehend the power of the visuals.
I fed PoliAI the most recent national presidential election poll. Emerson College performed the survey. I fed my AI machine the press release and the cross tabs and then started asking questions.
According to Emerson, “The first Emerson College Polling national survey following President Biden’s decision not to seek re-election finds Vice President Kamala Harris leading Donald Trump 50% to 46%. Five percent of likely voters are undecided. With undecided voters’ support allocated, Harris continues to lead by four, 52% to 48%. With third-party candidates on the ballot, Harris and Trump’s support evenly decreases by two points, Harris to 48% and Trump to 44%. Four percent support Robert F. Kennedy Jr.”
I wondered, however, how do the data points look visually? So, I asked Poli AI, point-blank, to explain to me why the political and non-profit industries should employ tables and charts to understand the political landscapes. I told it that there were professions such as campaign managers, journalists, candidates, non-profit leaders and others who would seem to benefit in being able to use the information in this format and asked it to further elucidate the issue.
This was its answer:
“These visuals give the political industry a powerful tool: that of turning complex data into clear, actionable insights. Journalists can use them for storytelling, while candidates and campaign managers can use them to identify voter priorities for message tailoring. Consultants can use the visuals to evaluate the power of strategies across demographics, and issue-oriented campaigns can identify which voter groups are most responsive to specific issues. These visualizations will enable political professionals to make data-driven decisions on who to target, how best to communicate information to constituents, what problems they can expect, and, most of all, opportunities. The charts thus help turn raw data into a strategic asset, making it easier for stakeholders to navigate the minefields of modern political campaigns.”
So rather than bore you with the “he said, it said” dialogue in which I prompted my pal to create those pictures, I will post the results and the AI’s explanations for each visual. I think you will find this so very useful. Here are the summaries, images and datasets and reasons these images are valuable.
Voter Motivation vs. Candidate Support by Age
Cross-tabulate the level of voter motivation with support for Harris or Trump, to show which candidate has more committed supporters.
Here is the chart showing the relationship between voter motivation and candidate support for Kamala Harris and Donald Trump based upon age. It reveals how each candidate's support varies based on the level of voter motivation. This visualization can help identify which candidate's supporters are more committed and how that might influence the election outcome.
Issue Importance vs. Candidate Favorability by Age Group Description
I wanted to see how far we could take the election inquiries. I asked Poli AI to cross reference a combination of the variables. It told me that my request was more difficult but we proceeded to tax the system. I wanted to view the same information but using different perspectives. Poli AI obliged and we settled upon the Group Bubble Chart and the Group Bar Chart.
These charts could show how favorability ratings for a candidate vary by both issue importance and age group.
The group bubble chart is set up so each bubble represents an age group, with its position indicating how important an issue is to that group, and the bubble size showing the favorability rating for a candidate within that age group on that issue.
First, here are the data points and then, the Bubble Chart.
USING GROUP BAR CHART
For comparison purposes, here are the same data points and the Group Bar Chart. Again, this visualization helps to clearly see how support for each candidate varies by both the importance of different issues and the demographic factor of age. It’s a more detailed and layered view of the data.
Issue Importance vs. Candidate Preference
How do the issues benefit and/or hurt the two candidates? We used two different graphs to convey the answers--Stacked Bar Chart and the Bubble Chart.
Stacked Bar Chart: This visual allows us to show the percentage of voters who prioritize each issue (e.g., economy, healthcare, immigration) and how they split between Kamala Harris, Donald Trump, and potentially other candidates. It makes it easy to compare across issues and see which candidate is favored by voters concerned with specific issues.
Below is the bubble chart that illustrates the relationship between issue importance and candidate preference. This is using the same information as the stackbar chart In this chart:
The horizontal axis represents the importance level of each issue.
The vertical axis shows the percentage of voters preferring each candidate.
The size of the bubbles represents the proportion of voters supporting each candidate for that specific issue.
This visual allows you to see not only how important each issue is to voters but also which candidate benefits most from voters who prioritize that issue.
Favorable Ratings of the candidates--Harris, Trump, Walz and Vance
Below is the grouped bar chart comparing the overall favorability ratings of Kamala Harris, Donald Trump, Tim Walz, and JD Vance. This chart allows you to easily compare how each figure is perceived across different favorability categories ("Very Favorable," "Somewhat Favorable," etc.).
This visual provides a clear side-by-side comparison, highlighting differences and similarities in public perception of these political figures
Issue Importance vs. Candidate Favorability by Age Group Description
I wanted to see how far we could take the election inquiries. I asked Poli AI to cross reference a combination of the variables. It told me that my request was more difficult but we proceeded to tax the system. I wanted to view the same information but using different perspectives. Poli AI obliged and we settled upon the Group Bubble Chart and the Group Bar Chart.
These charts could show how favorability ratings for a candidate vary by both issue importance and age group.
The group bubble chart is set up so each bubble represents an age group, with its position indicating how important an issue is to that group, and the bubble size showing the favorability rating for a candidate within that age group on that issue.
First, here are the data points and then, the Bubble Chart.
USING GROUP BAR CHART
For comparison purposes, here are the same data points and the Group Bar Chart. Again, this visualization helps to clearly see how support for each candidate varies by both the importance of different issues and the demographic factor of age. It’s a more detailed and layered view of the data.
So, why is all this visualization even important? I told Poli AI that certainly one could just look at the numbers and come to the same conclusions. I asked it to provide more details as to why waste one’s time on these colorful images? This was its response:
Certainly! Visual presentations of data, such as the charts and graphs we've created, offer several key advantages that make it easier to navigate the complexities of information in political campaigns:
Immediate Insights:
Visuals allow for quick identification of patterns, trends, and outliers that might be buried in raw data. For example, a bar chart can immediately show which issues are most important to specific age groups, which would take much longer to discern from a spreadsheet of numbers.
Simplified Comparisons:
Comparing multiple variables across different categories is much easier with visuals. In a grouped bar chart, for example, you can instantly compare candidate favorability across different issues and age groups side by side, something that would be cumbersome to do in a table format.
Engagement and Retention:
Visuals are more engaging than raw data. They can hold the viewer's attention longer, helping to ensure that key insights are not only communicated effectively but also retained. This is crucial in the fast-paced environment of political campaigns, where decisions need to be made quickly.
Enhanced Communication:
Visuals transcend technical knowledge, allowing non-experts (e.g., campaign managers, volunteers) to understand complex data without needing advanced analytical skills. This democratizes data insights, enabling more team members to contribute to strategy discussions.
Strategic Storytelling:
Visuals can be used to tell a compelling narrative that aligns with campaign goals. For example, a candidate might use a chart to show that they resonate strongly with young voters on healthcare issues, creating a targeted messaging strategy based on that insight.
Data-Driven Decision Making:
By making complex data more accessible, visuals empower campaigns to make decisions that are truly data-driven. Instead of relying on intuition or fragmented data points, campaigns can see the full picture and act with confidence.
In summary, while raw data provides the foundation, visualizations turn that data into a tool for strategic decision-making, making it easier for campaigns to identify opportunities, address challenges, and communicate effectively with their audience.
