SecurAI in media

Unemployed people considered “lazy” and “losers” in Finnish Twitter conversations, to the surprise of an American media researcher

April 16, 2021

Original article by Eleonoora Riihinen Helsingin Sanomat 3.4.

Unemployed people considered “lazy” and “losers” in Finnish Twitter conversations, to the surprise of an American media researcher

According to a recent study, in Finland, unemployment is talked about in a simplistic manner, and in a way that blames the individual.

Lazy, losers, slugabeds. Speech related to the unemployed on social media is largely stigmatizing and employees imagery laden with stereotypes.

These results are found in a study by the Finnish Unemployment Fund (YTK) and SecurAI Oy, a Helsinki-based firm which conducts artificial intelligence-based analyses, which looked at thousands of Finnish Twitter messages from 2006–2021.

One of the founders of SecurAI, an American media researcher, Dr. Mark West, describes the results of the analysis as surprising.

“I really wasn’t expecting that the images associated with the unemployed in a Nordic welfare state such as Finland would resemble the polarized public debate in the United States  so much,” West says in a video interview.

In the study, the artificial intelligence tool extracted messages related to the unemployed and unemployment benefits from Twitter with a few keywords, which were divided into two categories based on how the unemployed were looked upon by those who wrote the Tweets.

The categories were divided according to whether the writer was able to identify with the unemployed’s situation and understand that they themselves could at some point be in the same situation, or whether they treated the unemployed as “others'', at whom it’s easy to direct emotional and negatively charged designations.

According to the analysis, 59 percent of those writing about unemployment were sympathetic towards the unemployed and understood unemployment primarily as a structural problem, whereas 41 percent considered unemployment to be a person's own fault.

In the latter category, the most common designations for the unemployed were “lazy” and “poor”. In addition to these, the words “loser”, “problem” and “worthless” were also used. These stigmatizing words were accompanied by clarifying or reinforcing attributes such as “fuss,” “punishing,” and “parasites.”

Among those who speak in such a manner, unemployment was also linked to immigration and the misuse of social benefits in general.

In his research and writing work, Mark West has explored the American media debate and the growth and impact of Internet culture.

It is noteworthy that the result of the survey was obtained from Twitter, where a significant proportion of the interviewers are so-called “opinion leaders”, i.e. people in the media and politics, who mostly write under their own names.

Is Twitter, however, an effective measure of the prevailing images? One could imagine that emotionally-laden expressions are emphasized, and that most messages are written in an emotional state.

According to West, the content on social media is a better measure of real opinions than, for example, telephone polls.

“In telephone surveys, people’s responses are biased towards a more socially acceptable opinion. This was seen, for example, in the polls’ inability to predict [Donald] Trump’s election victory [in 2016],” West says.

With the survey, YTK wanted to study Finns' perceptions of unemployment. The results were disappointing, says Ilona Kangas, YTK’s Director of Customer Relations and Communications.

“I have to say that when West told us about the results, it was even a little distressing. There was a feeling that something needs to be done immediately, because people's perceptions do not correspond to reality”, says Kangas.

First of all, the group of unemployed is diverse, Kangas points out. Simplistic ways of speaking about unemployment doesn’t adequately describe the phenomena associated with various forms of unemployment, from part-time work to temporary employment and light entrepreneurship.

“And, of course, the full-time unemployed don’t deserve such stigmas either,” Kangas says.

Tough language use about the unemployed is part of a bigger phenomenon that worries Mark West. Polarization and the othering of marginal groups is the result of a shift in the power of debate from traditional media to platforms driven by technology giants’ algorithms and their opinion leaders.

Communication that has moved to social media is more prone to opinion manipulation, as seen, for example, in the Cambridge Analytica scandal.

According to West, algorithms need to be better trained in the future to recognize various distortions, whether it is the recognition of hate speech or emphasises related to gender or ethnicity.



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