It went wrong….again?

In 2016, almost the whole world was shocked when Donald Trump won the election as the polls were declaring Hilary Clinton as the candidate that was most likely to win.  Pollsters faced a public backlash after this huge fail and promised to find and solve the errors in their methods. However, they did miss the mark again during the election of 2020. This year the polls expected strong leads in certain states for Biden, but in some of these states the difference between the two parties was very small. Thereby, the polls also predicted that Biden would win Florida. Instead, Trump won the state with a pretty big lead (NBC News, 2020). How could it happen again that the polls were making incorrect predictions?

Let’s have a closer look at what went wrong this year with the polls.

Three explanations

Pollsters don’t have a clear explanation yet for what went wrong, and it is likely that it will take some time before we know what exactly happened. However, there are already many possible explanations for the missteps. Some of these are based on the mistakes that were also made in 2016 and others are based on inside information from experts and scientists. In the upcoming alineas, three explanations will be given of what went wrong this year with the polls. 

Small sample size of  minority groups

The first explanation is the minority groups being not well represented in the poll samples.  According to Minority Rights (2020) 38,1% of the population living in the United States are part of minority groups. These minority groups include for example the Hispanic Americans and African American.

Camille Burge, Professor in Political Science at Villanova University, argues that the sample sizes of racial or ethnic minorities in the polls of 2020 are small. This also happened in 2016 (PRC, 2016). It could be explained by the fact that these people are harder to reach to make them fill in the surveys. Thereby, the individuals who are part of these minorities that do respond to the surveys are individuals who have a high educational attainment. Leading to a sample size that is not only incomplete but also biased. Which makes the sample not a good representation of the population. 

Combining this information with the theory of Wicherts (2017) you could conclude that sampling is part of the design phase. In his paper he argues that you should not exclude participants from your research in the design phase. However, in the case of the sampling for the election polls, that did happen. Not being explicit about your data and excluding specific groups, leads to an incomplete and non-representable sample. Making the sample and therefore the polls, misleading data.

Donald Trump effect

The second explanation is the so-called: ‘Donald Trump effect’. Since Donald Trump became president, he has systematically attacked the media and poll makers claiming they were only spreading fake and incorrect news. The incessant attacks led to his supporters believing Trump’s claims that the media was fake. Therefore, pollsters noticed that many Trump supporters did not want to reply to surveys (AAPOR, 2020). Simply because they are convinced that they should not trust the media and poll makers. Following Patrick Murray from the Monmouth University Polling Institute, are those Trump supporters called: Shy Trumpers. It is not that they are in fact shy, but they are simply less likely to respond to the pollsters and their surveys. This as a whole is called by Murray the ‘Donald Trump Effect’.

This ‘Donald Trump effect’ can be seen as a form of confirmation bias. Confirmation bias is described by Chamber (2017) as that: “We seek out and favor evidence that agrees with our existing beliefs, while at the same time ignoring or devaluing evidence that doesn’t”. The Shy Trumpers confirm their actions (not responding) with their beliefs (pollsters are fake). They don’t critically review if their actions are indeed right, because they blindly believe their leader (Kouzes & Posner, 1993).

Thereby you could also conclude that because these ‘Shy Trumpers’ did not respond as much as others to the survey. That this specific group was also not well represented in the poll samples. Making the samples again non-representable and therefore misleading. 

Polling firms

The third explanation is about the polling firms who executed the polls this year. Polling firms can help politicians gain insights into the opinions of a population. Politicians like to spend a big part of their campaign money on poll makers. However, the firms have been criticised for making profit and therefore maybe being biased (NBC,2020). 

An example of confirmation bias is the selection task theory by Wason (1968). In his paper he argues that we often tend to look for confirmation instead of falsification. The paper by Umphress, Bingham and Mitchell (2010) also indicate that when companies get rewarded by a client, they could feel a sense of reciprocity. This sense of reciprocity could lead to a company not feeling the urge to critically review their own poll and surveys after it has come to a positive result for the client. Concluding that the polling firms could also be biased themselves.

Conclusion

In the previous paragraphs three explanations are given to answer the question why the polls missed the mark during the 2020 elections. I would argue that the polls mainly made some errors during their sampling. Concluding that it is not the sample size that makes a poll representative, but the sampling that makes a poll representative. If sampling is not done sufficiently and specific groups are not included in the sample, the sample becomes incomplete and not representative. Together, this makes a poll a form of misleading data that is presented and broadcast via the newspapers and news stations. Leading to many people receiving wrong and misleading data, on which they base their opinion. 

After reading this blog, how do you feel about the polls? Do you think they are trustworthy? Let me know in the comments!

References

American Association for Public opinion Research. (n.d.). 2020 Pre-Election Polls: Performance of the Polls in the Democratic Primaries – AAPOR. Retrieved November 11, 2020, from https://www.aapor.org/Education-Resources/Reports/2020-Pre-Election-Polls-Performance-of-the-Polls-i.aspx

Chambers, C. (2017). The 7 deadly sins of psychology. A manifesto for reforming the culture of scientific practice (Chapter 1: The sin of bias). Princeton, NJ: Princeton University Press.

Feiner, L. & CNBC. (2020, November 7). Pollsters face another reckoning this year, but the reasons could differ from 2016. Retrieved November 12, 2020, from https://www.cnbc.com/2020/11/07/election-pollsters-2020-reckoning.html#close

Kouzes, J. M., & Posner, B. Z. (1993). Credibility (Vol. 11). San Francisco: Jossey-Bass.

Linge, M. K., Lewak, D., & New York Post. (2020, November 10). Why election polls were so wrong again in 2020. Retrieved November 10, 2020, from https://nypost.com/article/the-real-reason-election-polls-were-so-wrong-again-in-2020/

McBride, K. (2020, November 4). What went wrong with the 2020 election polls and what’s next for political polling? Retrieved November 10, 2020, from https://www.poynter.org/reporting-editing/2020/what-went-wrong-with-the-2020-election-polls-and-whats-next-for-political-polling/

Mercer, A., Deane, C., McGeeney, K., & Pew Research Center. (2016, November 9). Why 2016 election polls missed their mark. Retrieved November 12, 2020, from https://www.pewresearch.org/fact-tank/2016/11/09/why-2016-election-polls-missed-their-mark/

NBC News. (2020, November 12). Live 2020 election polls: Who is leading the presidential race? Retrieved November 12, 2020, from https://www.nbcnews.com/politics/2020-elections/presidential-polls

Umphress, E. E., Bingham, J. B., & Mitchell, M. S. (2010). Unethical behavior in the name of the company: the moderating effect of organizational identification and positive reciprocity beliefs on unethical pro-organizational behavior. Journal of applied psychology, 95(4), 769.

Wason, P.C.(1968). Reasoning about a rule. Quarterly Journal of Experimental Psychology 20, 273–281.

Wicherts, J. M., Veldkamp, C. L., Augusteijn, H. E., Bakker, M., Van Aert, R., & Van Assen, M. A. (2016). Degrees of freedom in planning, running, analyzing, and reporting psychological studies: A checklist to avoid p-hacking. Frontiers in psychology, 7, 1832.

Can famous Dutch people be trusted as your daily information source about COVID-19?

The era of media communication tools
The COVID-19 pandemic has caused resistance towards authorities and governments all around the world. Also, in the Netherlands; the government has implemented rules and restrictions on its citizens including closing theatres, closing restaurants, and only allowing a maximum number of people in one space etc. During the summertime, a number of famous Dutch people (BN’ers) collectively decided that they did not want to adhere to the Corona measures anymore. They started the hashtag “#FreeThePeople” and communicated this via their social media accounts. In these posts, they called their followers to action, instructing them to stand up against the governmental measures.
Nowadays, it has become easier for (famous) people to share their opinions and beliefs about a certain topic with others due to a wide variety of mobile media communication tools. More specifically, famous people can reach mass audiences with just one post on Twitter, Instagram, Facebook or YouTube. In fact, Famke Louise (one of the initiators behind the #FreeThePeople-hashtag) has the ability to reach one million followers on Instagram. Although this is not necessarily something bad. What are the consequences if these famous people start spreading fake news or misinformation? Well, they are able to shape the opinions and beliefs of mass audiences with regards to a certain topic, in this case, the COVID-19 measures. And that could be concerning. Therefore, we decided to investigate if and to what extent famous Dutch people are spreading misinformation or fake news about COVID-19. We scoped our research in such a way that we included famous Dutch people such as Tim Hofman, Peter R. de Vries, and Maurice de Hond, who often appear in popular media. We decided to exclude Dutch politicians, even though they do often meet the benchmark as popular media figures. However, they might already be biased due to the political party they represent.

To investigate if and to what extent famous Dutch people spread misinformation and fake news about COVID-19, we selected a subset of 38 tweets in total. Overall, we fact-checked the text, videos, images, and links the tweets contained. For every tweet, it was indicated whether the tweets were based on facts or not, using the categories borrowed from Politifacts ‘Truth-o-meter’. For further explanations about the fact-checking approach, we highly recommend you to read our report here

What did we find? 
We found that only 55% of the subset of tweets can be labelled as “totally true” or “mostly true”, which is quite shocking considering the fact that almost all the accounts we fact-checked have over ten thousand followers. Moreover, approximately 34% of tweets can be labelled as “half true”, “mostly false”, “false”, or “pants on fire”. Furthermore, we found that approximately 11% of the tweets could not be linked to conforming/contradicting evidence. 

One general pattern we found is that a lot of information provided in the tweets is partially accurate, but lacks important details or additional information with regards to the context. For example, Jan Roos tweeted about the Coronavirus Response Investment Initiative by the European Commission stating that Morocco, Tunisia, and Ukraine received funding. However, this can’t be traced back to the original source. On the other hand, Jan Roos’s tweet contains accurate information about the funding of other European countries. Similarly, Arjen Lubach tweeted a video from his show “Zondag met Lubach” in which he explains the spreading of the Coronavirus among minks in The Netherlands. Most of the statements in this video are accurate, however; two of them are false; minks can infect humans, and raccoon dogs can get infected with COVID-19 and thereafter infect humans. In fact, it isn’t confirmed that minks or raccoon dogs could infect humans with the Coronavirus. Hell, it isn’t even confirmed that raccoon dogs can become infected at all. This shows that even a team of professional journalists can be guilty of spreading misinformation. In total, we found 17 tweets that had partially accurate statements but lacked important details, additional information, or even made additional false statements.

It is also important to highlight that we found some examples of dangerous misinformation spread by famous people in relation to COVID-19. For instance, Jack van Gelder, with more than 150.00 followers, quotes another Dutch celebrity, André Hazes Jr. In these quotes, Andre Hazes Jr. mentioned that the COVID-19 is comparable with the flu and that we should still shake hands and attend parties. Andre Hazes Jr. based these statements on false information on the website OffGuardian, this site is known for spreading misinformation regarding COVID-19. Moreover, through research, it has become clear that the COVID-19 virus is ten times deadlier than the Influenza virus. Therefore, Andre Hazes Jr.’s advice is not only misleading but also dangerous as the COVID-19 virus is transmissible through close-contact. Likewise, Maurice de Hond, who has more than 100.000 followers, tweeted two statements on April 20, 2020, which roughly translate to: ‘the virus cannot be transmitted through objects’, and ‘It is false that when you wear a mouth mask, and take off that mouth mask, you can subtract the virus from droplets on the mouth mask. Maurice de Hond’s statement is based on research conducted by Hendrik Streeck, a German virologist/professor of the Institute of Virology at the University of Bonn. Although his research is accepted by other virologists, nuances have been made about the topic. Different sources like the CDC, RIVM, and the WHO suggest that there is a chance that people get COVID-19 from contact with contaminated surfaces. More importantly, research was still ongoing at the time. Hence, the statements in Maurice de Hond’s tweet can be seen as premature and dangerous misinformation, since he has a large audience to which he can target. Overall, we found 6 tweets that contained an element of truth but ignored critical facts, were totally inaccurate or made ridiculous claims.

In contrast, we also found a substantial number of tweets that contained little to no misinformation. In fact, Diederik Jekel tweeted a video in which he explains the Coronavirus in “normal human language”. This video is not manipulated in any way and therefore helps people to understand the (sometimes difficult) information provided by the government. Also, he explains which consequences can occur if people do not adhere to the governmental measures. All of the information in the video can be seen as accurate, and it is actually very informative. Even though it remains up to the viewers to act upon this video, it at least is a nice example of trying to use mobile media communication to spread accurate, helpful information with regards to COVID-19. In total, we found 11 tweets that were accurate and did not miss any significant information. 

What now? 
Most of the Dutch celebrities were telling, for the most part, the truth. However, some Dutch celebrities did not think rationally and did not make a thoughtful decision with (re)tweeting misleading information, a bit of an oxymoron. Those celebrities that were spreading misleading news regarding COVID-19 varied in severity. The most severe tweets of celebrities are the ones that undermine or share conspiracy theories regarding COVID-19. The spread of misleading information and conspiracy theory can cause harm to the people that follow these celebrities on social media. On the other hand, there are also many Dutch celebrities that tweet (mostly) truthful information about COVID-19. These tweets are mainly about the dangers of COVID-19, urging people to stay home or to follow the guidelines of the government. However, as we see on “regular” social media, different views of COVID-19 are noticed as this does not differ with Dutch celebrities. Therefore, we conclude that a lot of the tweets are a combination of the people’s own opinions and a confirmatory piece of information. Because the tweets are a mix of those two, we can say that most of these people do not have bad intentions when it comes to spreading information, which in some cases was false and misleading. A good example was the tweet by Thijs Zeeman. He mentioned that his information was from a Dutch journalist, but this journalist responded on the tweet saying it was not him. Thijs apologised and said that his tweet was a good representation of his own situation. So, a good example of a lack of accuracy and confirmation bias. Referring back to our findings, it does not have to be an extremely bad thing that approximately one-third of the tweets were founded as half true, mostly false, false, or pants on fire. The bigger problem is that these famous Dutch people are not accurate enough when (re)tweeting information. These people can reach a large number of followers, which eventually could have consequences for society as a whole. Therefore, it is important that they learn to be more critical about the information they want to share and eventually, there will be more tweets that can be labeled as completely true. 

Take your pills – A blog about framing

Picture 1 – Ready for the winter

Winter is coming up and so are also the advertisements for vitamin supplements. You can’t unsee them these days. Commercial breaks, social media ads and leaflets are packed with these advertisements. As can be seen in picture one, the drugstores really want to ensure that you will get through the winter time. They are eager to help you with that and their provision is: vitamin supplements. 

Way before the winter days start, the drugstores paint a picture that everyone needs vitamin supplements. They are trying to attract your attention with some salient quotes like: Boost your immune system! Or Purchase your immune system now and keep staying healthy! If you look a little closer to these quotes, it is striking that these are focused on the benefits of the products and how they can help you. Nowhere in the advertisement or on the packaging can be found any disadvantages or possible risks. Are these quotes maybe a smart way of framing a product?

Let’s have a closer look into this. 

Picture 2- Boost your immune system!

 What is framing? 

Framing is described by Entman (1993) as follows: “Framing essentially involves selection and salience. To frame is to select some aspects of a perceived reality and make them more salient in a communicating context, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described”.

You could say that framing is the way of how a message is designed and how this leads to a certain interpretation. A commonly used way of framing is equivalence framing. According to Kahneman & Tversky (1979) is equivalence framing about “the different presentations of essentially identical decision making scenarios influence people’s choices and their evaluation of the various options presented to them”. 

This ‘way of presenting’ are often wisely chosen words. As can be seen in picture two, the advertisement says: Boosts your immune system. The text is not saying for example: A lower chance to catch a cold. This specific decision on words is a good example of the loss and gain frame. This framing theory includes that the way of communication could be framed in terms of advantages or disadvantages (Ratcliff, Jensen, Scherr, Krakow and Crossley, 2019). Hereby, are the advantages the gain frame and the disadvantages the loss frame.

Picture 3 – Vitamine C 1000mg supports your immune system.

Carefully picking the words

Clearly, the drugstores choose the gain frame in their advertisement for the vitamin supplements. The same applies to the packaging of the products (see picture 3). The way of communication is always positive, including words that emphasize the advantages of the product. Commonly used gain framing words in vitamin supplements ads are: boost, support, strengthen and help. These framed words can have a big influence on the attitude of the customer toward the product (Segev, Fernandes and Wang, 2015). When an attitude is positive towards a product, there is a higher chance that someone will buy the product. Considering that, is framing a fair way of communication? Knowing that disadvantages are not clearly shown. Stated differently, do drugstores risk an increment of their sales over the health of their customers by not clearly communicating disadvantages?

Criticism

In 2013 the Dutch Television program Kassa published a blog in which they questioned the way of how information is coming short on the side effects of vitamin supplements. They argue that the drugstores are not well aware of the recommended daily amount and the harmful side effects of high dosages. Resulting that their advertisements and information on the packaging is incomplete.

Also, the Dutch health council (De Gezondheidsraad) brought out an advice about the intake of vitamin supplements saying: “The Committee concludes that a good and varied diet is sufficient to provide the general, healthy population with enough micronutrients.That is why only certain risk groups require extra of some micronutrients in addition to a varied diet. Vitamin supplements are not necessary for people outside of these risk groups”.

Illusions

“Often the illusion is being created that people are not getting enough vitamins and minerals.”, says Dr. Jeanne de Vries, nutrition scientist at Wageningen University & Research. Thereby, she argues that a lot of people have vague symptoms, which they think they can solve with a high dose of vitamin supplements. Not being aware that this high dose is potentially very harmful. This illusion is often created by advertisements. As mentioned above, it is often an advertisement saying: “Boost your immune system this winter, take vitamin C”. Leading to people taking a high dose of these vitamins, which they think will ‘boost’ their immune system. However, it instead could lead to intestinal or kidney complaints. 

Concluding

The advertisements for vitamin supplements are made as appealing as possible, including wisely chosen gain framed words. However, this gain framing leads to people only being confronted with the advantages of the supplements.The risks and side effects are often not visibly communicated, leading to people being not completely informed about the supplements. Therefore, I would argue that these advertisements and quotes lead to (healthy) people taking a supplement that is not necessary for their health system. Caused by the created illusion of advertisements that these vitamin supplements will only benefit you. Shouldn’t the advertisements also visible communicate the disadvantages or side effects to prevent any unnecessary complaints? Or is it their prerogative to only advertise with the benefits? 

I would like to hear your thoughts on this. So, let me know in the comments!

References 

Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51-58.

Kahneman, D., & Tversky, A. (1979). On the interpretation of intuitive probability: A reply to Jonathan Cohen.

Kassa. (2013, December 14). Voorlichting bijwerkingen schieten te kort. Retrieved November 5, 2020, from: https://www.bnnvara.nl/kassa/artikelen/voorlichting-bijwerkingen-vitaminen-schiet-tekort

Lareb. (2013, April 6). Adviezen gezonde voeding naar een voldoende inname van vitamines en mineralen. Retrieved November 5, 2020 from: https://www.gezondheidsraad.nl/nl/adviezen/gezonde-voeding/naar-een-voldoende-inname-van-vitamines-en-mineralen

ONVZ. (2020, June 12). De zin en onzin van vitaminepillen. Retrieved from https://www.nrc.nl/advertentie/onvz/de-zin-en-onzin-van-vitaminepillen

Ratcliff, C. L., Jensen, J. D., Scherr, C. L., Krakow, M., & Crossley, K. (2019). Loss/gain framing, dose, and reactance: a message experiment. Risk Analysis, 39(12), 2640-2652.