WHAT IS POLL HERDING 

Poll herding is a practice where polling organizations adjust, suppress or change their result to fit or look similar to what others are reporting. This is done to avoid being the odd one and fear of being criticized. Poll herding makes the results look similar, reduces the real insight of the polls because duplicating other people’s poll eliminates its authenticity and this in turn makes it hard to differentiate the real numbers from a copied poll.

WHY POLLSTERS HERD

Pollsters herd because of the fear of being the odd one, being criticized and this usually happens when an election is getting closer as this increases and shifts the attention on the polling and polling results.

• Fear of being different: No one wants to be an odd one. If a pollster’s result is different from others, they get criticized so instead of allowing this to happen, they adjust their result to match others. If the general consensus is wrong, everyone gets the blame.
• Protect their image: Pollsters need customers to make money. If they publish a result that is different from the general consensus, it can alter their brand image and people would think they are not good for the job.
• The secret change: When pollsters discover their result is different from the general published result, pollsters may quietly change their result to make their numbers similar to others.
• Same information: Pollsters may have studied past elections, voting results, and public opinion. Apply the same methodology can make their final results looks similar.

THE METHODOLOGY 

Methodology plays a crucial role in poll herding, the way a poll is written, constructed and designed plays a huge role in the outcome of its final results. When pollsters use similar methods, the result may naturally become alike.

• Sampling: Pollsters choose a group of people to represent the wider voting population. Similar sampling approaches can produce similar results.
• Weighting: Pollsters may adjust results to fit the general expected population. Using a similar weighting method can bring the results closer together.
• Question wording: Slight differences in how questions are designed and asked can alter responses. When similar wordings is used, results may end up being similar.
• Mode of collection: Methods through which the polls are conducted either through survey, one-on-one or other methods can influence how many would participate and what their response would be.
• Data adjustments: Pollsters may adjust their result to correct past voting behaviors or differences in the sample.

WHY OUTLIER POLLS MATTERS

Outlier polls are polls that are noticeably different from the general consensus. They are important because they may reveal and provide useful information about possible changes in public opinions, but they can also reveal methodological differences or sampling error in the polls

• They question the general opinion: An outlier poll can reveal that the general polling picture may not be as clear as they appear.
• They show differences in the approach: The results can be different because of who they choose to vote, how they calculate the results or how they choose who is going to vote.
• They can expose poll herding: If pollsters always alter their result to fit the general consensus, they would check if there is a good reason to do that or just follow others.
• They can spot new trends early: Sometimes an odd result is the first sign that people’s opinions are really changing.
• They reveal there is still uncertainty: Instead of accepting that a group of similar polls show exactly what people are thinking, an odd result reveals that even when polls look alike, they may not be exactly right.

HOW POLL HERDING AFFECTS PUBLIC OPINION

Poll herding can affect public opinion. When people see the same number repeatedly, they may believe the numbers to be true more than it really is.

• Create a sense of agreement: Similar polls would make people believe that the opinion is uniform and firmly settled in the same way.
• Forms media coverage: News organizations and media reports may focus more on the general trend while giving little or no attention to polls that produce different results.
• Influences views of candidates: Repeated polling numbers can affect how people view a candidate’s level of support and influence in the race.
• Alters voter expectations: People may assume or develop expectations about how an election is likely to happen based on the general consensus.

HOW TO IDENTIFY POLL HERDING

Identifying poll herding goes beyond checking for final numbers only, how the polls were counted and how the numbers changed over time.

• Check for unusual similar results: If a large number of independent polls repeatedly produce similar figures, then there is a need to check for why.
• Look for unusual adjustments: Big changes between the raw survey results and the published estimates may need a close look especially when they are moving towards the general polling consensus.
• Examine methodology: Compare sampling, weighting, question wording, and data-collection methods used across pollsters.
• Check the timing: Compare when each poll was carried out. Polls conducted at separate times may legitimately give different results because public opinion can change.
• Look for repeated patterns: Identifying poll herding cannot be tied to just one similar result; rather a repeated and consistent pattern of pollsters moving toward the same range needs to be checked.

HOW RESEARCHERS CAN REDUCE POLL HERDING 

Researchers can reduce copied polls by making their polls method more clear, open and steady. This can achieved by doing the following:

• Use independent methods: Researchers should develop their own sampling and analysis methods even if their results are different from other polls rather than using previous methods of the past.
• Pre-register methods: They can document their sampling plans, weighting procedures, and analysis methods before collecting data. This makes it easier to identify changes made later.
• Be transparent: They should openly explain how the poll was conducted, who was asked, how many people participated and how the answers were counted. This would help check if the poll is real.
• Explain adjustments: If any adjustment was done to the polling results, researchers should clearly explain what was altered and why it was done.
• Compare results after publication: Researchers can evaluate the difference between their findings and other polls without altering their own estimates to match the consensus.

CONCLUSION

Poll herding happens when different polls show almost the same results. This happens when pollsters use the same methods or copy each other’s adjustments. Polls can look similar when they are asking the same people, but when they are too similar, it hides the fact that we can’t be 100% sure of what people really think.

To fix this, researchers should use their own independent methods, clearly explain any changes they make, and be honest about the fact that polls can have errors.When they do this, it helps understand the results better and serve as a reminder not to see similar polls as perfect proof of what will happen.