A worm poll is a poll which is conducted to generate realtime data about audience responses to an event, typically a political debate. The data is used to generate a graph of viewer approval, which can look sort of like a worm inching along, rising and falling in response to the debate or speech. While worm polls do not always provide accurate pictures of public response to speeches, they can be used to create a basic yardstick of viewer response, which can be extremely useful for politicians who think quickly on their feet.
The data used in a worm poll is generated by handsets held by viewers of a debate which may be live or televised. As they watch the debate, viewers can indicate their approval or disapproval of what is being said; with large numbers of viewers to create a big sample, the data can be quite interesting. In some instances, the viewers may be broken up by political leaning, gender, or other criteria, to learn about how specific groups respond to political topics.
Often, worm poll data is displayed on television as debates are broadcast, and this can be interesting for home viewers. It is possible to observe radical rises and falls in opinion as particular topics or even words come up. Adaptable politicians take note of the continuous survey data from the worm poll to adjust their stance or approach to the debate, in the hopes of keeping their numbers off.
Because the data in a worm poll can fluctuate so radically, a worm poll isn’t always the best way to judge responses to a speech or debate. For example, people’s opinions of the politicians may change after reflection, or after reading commentary on the debate, and sometimes the overall perception of a politician’s performance can be contradict the results obtained over the course of the worm poll.
Analysis of worm polls is only one part of a political campaign, but these polls can be powerful tools. By learning about the gut reactions of audiences to particular styles of speechmaking and topics, political advisors can make suggestions for future events, identifying points where a candidate is perceived as weak so that the team can work more explicitly on these areas.