Francisca Ortiz, PhD researcher in the Department of Sociology, School of Social Science, at The University of Manchester. Email: franortizruiz@gmail.com or francisca.ortiz@manchester.ac.uk

Louise Mitchell, PhD researcher at the School of Science, Engineering and Environment, at The University of Salford. Email: l.m.mitchell1@salford.ac.uk


The focus of our research is to study the social stereotypes of older people during the Covid-19 pandemic, with a specific focus set across the United Kingdom (UK) and its vaccination programme. The study of ageism has been largely advanced in gerontology, with many pre-existing studies exploring the concept of ageism, and its different definitions that precede discussion (Nelson, 2002; Brownell and Kelly, 2013; Gullette, 2017; Ayalon and Tesch-Römer, 2018). Yet, there remains a gap reflecting on ageism felt across the Coronavirus crisis.

Arguably the first academic to introduce the concept of ageism, was Robert Butler in 1969 as a notion similar to racism and sexism (1969, 1975). His definition suggests it is: “a process of systematic stereotyping and discrimination against people because they are old” (Butler, 1995: 35). Erdman Palmore (1999) went on to relate this concept to broaden the discussion, to incorporate the negative and positive stereotypes that are constructed around the ageing population. He started his book with these words: “Ageism has been called the ultimate prejudice, the last discrimination, the crudest rejection” (1999: 3), making a powerful statement about the injustice that ageing populations face. In 2001, Formosa declared that to solve the issue of ageism in society, we must look towards solving it as a political question, by taking a “critical reflection on how older persons are being oppressed and discriminated against based on their old age” (22). This research tries to extend the knowledge about the topic in the 21st century, and then, prevent inequalities by recommending suggestions of resolution.

Ageism can be considered a social construct, that humankind has created, established by social powers, influenced by how they are portrayed in society – whether that be through internal personal opinions generated, or manipulated through external means such as the media (newspapers, media broadcast, social media, etc.). The relevance of studying newspapers is that these documents inform the general population about what is happening in society. However, it is well-known that the news is influenced by the people who write about them, having a significant impact in how the general public perceive and accept these stories, all while consequently impacting populations in which they are written about. Current research highlights how the newspapers discourses maintain a vision about retirement, which is considered to have been written from a government perspective within neoliberal rationality and hiding other injustices of the system (Rudman, 2005). The presence of ageism within the media tends to adopt a negative stereotype surrounding the ageing population, misrepresenting a diverse and vibrant population (Loos & Ivan, 2018). This has had an impact on people’s discourses too, leading to the media enforcing stereotypes, prejudice and discrimination by pushing negative connotations, particularly across frailty and declining health. It should be considered that this does not mean that the readers do not have the capability of choosing what to believe, although it is clear there is power and influence in the depiction of older people in the media. In the times of the pandemic, older people have been singled out in a multitude of manners; due to a vulnerability of dealing with the virus (e.g., shielding category), complexities of dealing with aftereffects (comorbidities), those living in care environments (excess deaths alongside home visitation allowance/stipulations (see Milne, 2021), and the subsequent roll out of the vaccination program.

As our face-to-face interactions decreased because of the implementation of lockdowns, many people turned to and relied on social media for these interpersonal relations (Masciantonio et al., 2021). The time we spend online often brings both positive and negative health impacts, by constructing opportunities to engage with others in different ways, alongside advances such as following social media trends (e.g., TikTok dances, fundraising challenges). Yet, as we turned to social media in the time of the pandemic various negative outcomes became apparent including the spread of misinformation and denial of scientific literature (Rosenberg, Syed & Rezaie, 2020), alongside facilitating an undercurrent of ageism and a rise in vaccine hesitancy (Dube, et al., 2016).

To understand more about this concept, combining ageism alongside the pandemic vaccination, we established a research question asking: “are there any negative stereotypes about older people in the public discussion about the vaccine for Covid-19 through tweets? Which ones are they?”

To do so, we revised literature about ageism in discussion around Covid-19, which in turn helped us to decide to focus the analysis on Twitter, as an open platform where the general public can express views. The data collected was those tweets around specific hashtags related to ‘vaccination’ and ‘covid’ (and similar),  across three selected dates: (1) when the Oxford vaccine was approved, (2) when the plan of vaccine distribution was announced, and (3) the day of the first vaccination in UK.

In the frame of this research, we identified some difficulties, benefits and limitations of using this type of data for understanding ageism on Twitter at a deeper level. Next, we will share each of those, which we feel may be useful for future studies on the topic.

Difficulties

The first challenge for many within research, and specifically using social media, is ethics. Depending on the institutions and country in which you are doing your study, those ethics requirement can vary dramatically. In some institutions demographic data is deemed to be private; but in others, it is public data, causing anonymity difficulties. In the case of this study, it took considerable amounts of time to gain clarification on the level of ethics required from the funding university, with the final decision suggesting no formal application was required (other similar studies were in similar situations, see Bonnevie, et al., 2020). Also, depending on the tool used for collecting the data, some automatically collect demographics, which makes cleaning and anonymising more time consuming. In fact, collecting the data could mean 10-20% of the time, while the other 80-90% is cleaning. It is challenging start working for the first time with this data, but once you learn, it is become easier.

Benefits

Many times, it is difficult to access the stereotypes existing in society about older people through interviews, as the participants need to have trust in the researcher. This is a challenging and sometimes barriers are unable to be broken down. Yet, analysing social media is like investigating documented versions of those beliefs. Then, this provides an interesting approach to understand social stereotypes and the discourses of the digital world – especially useful for exploring ageism, and across different generations of users of social media.

Currently, we are still living in a world shaped by a pandemic, and that makes collecting data difficult. However, using tweets as source of information enables accessibility even though the existences of COVID-19 restrictions.

In general, this type of research is constructed and shared by platforms like GitHub, in which you can find many studies that already worked with this type of data using codes. They liberate those codes, and anyone could replicate their methods. Obviously, that decision depends completely on the researchers, as not all of them choose to make their information open access afterwards. Even though, there are many already in the community who share their advances and collaborate on doing these processes clearer and more open for all.

Concluding this section, another benefit illustrates that social media data is something that you could also take from a relational point of view. In other words, it could be analysed the way in each word related with others, or how influencers used their networks to spread their thoughts. We all live in societies that are formed by relationships, and those aspects are translated to the digital world; which at the end may had an impact on the reality of people, or social media could act as an extension of that reality.

Limitations

To conclude, we identified three main limitations of this approach. Firstly, the data collected and analysed is within a digital world, and in this sense is not the reality. When we are using this type of information is incredible useful to have access to different aspect of life, although it is not everything, as people’s opinions expressed online often differ significantly to those expressed in real life. Researchers needs to always have this limitation in mind when working with tweets. Secondly, hashtags used in studies cannot access all the views held around the topic. The number of tweets allowed to collect differs of the type of permission by twitter (API) that you have. In other words, it is the type of results that we could have depends of the tools used. Finally, there could be importance held within the demographics of those tweeting, such as gender, age, race, among others; therefore ethical approval could be sought to include these matters into future studies. Missing this information could be crucial for some research questions, and ultimately influencing the ability to reduce ageism in the future. 


Acknowledgement

This research project is titled “Ageism in the era of Covid-19: exploring stereotypes in the press and/or social media” and has been funded by MICRA Seedcorn Funding Call for 2021. Funding was co-awarded to the researchers Francisca Ortiz and Louise Mitchell between January – September 2021. Alongside, both researchers have received support to conduct PhD studies, not directly influencing/ related to this research; from the National Chilean Agency of Research and Development ANID [2018 – 72190281] and the University Alliance: Doctoral Training Alliance (DTA). Therefore, these financial sponsors do not have direct influence in this study, and results may not reflect opinions held by these organisations, nor by MICRA.


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