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Recommendations to support interaction with broadcast debates: a study on older adults’ interaction with The Moral Maze

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Abstract

Current methods to capture, analyse and present the audience participation of broadcast events are increasingly carried out using social media. Uptake of such technology tools has so far been poor amongst older adults, and it has the worrying effect of excluding the demographic from participation. Our work explores whether a common desire to interact with debates can be tapped with technology with a very low barrier to entry, to both support better engagement with broadcast debates and encourage greater use of social media. This paper describes experiments where older adults interact with a BBC radio debate programme: The Moral Maze. As a result, we obtained common interaction patterns which then are used to define recommendations for software-supported interaction with debates based on theories of argumentation. Our goal is to combine research on computational models of argument and user-driven research on human-centred computing in a project with the potential for high-profile impact in addressing older adults inclusion in the digital economy.

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Notes

  1. We consider older adults as persons over 65 years old without distinguishing based on cognitive or physical conditions.

  2. http://www.bbc.co.uk/shows/moralmaze.

  3. Question Time (TV, BBC1), Free Speech (TV, BBC3), The Big Questions (TV, BBC1), Sunday Morning Live (TV, BBC1), The World Debate (BBC News), Brian Taylor’s Big Debate (BBC Radio Scotland), The Moral Maze (BBC Radio 4) and The Intelligence Square Debate (BBC World News).

  4. http://www.nielsen.com/us/en/newswire/2012/final-presidential-debate-draws-59-2-million-viewers.html Accessed June 2014.

  5. http://www.digitaltrends.com/social-media/the-internets-reaction-to-last-nights-presidential-debates Accessed June 2014.

  6. Sentiment Analysis (Pang and Lee 2008) is the process of analysing human expressions (in the form of text mainly) with the use of natural language and computational linguistic processes in order to extract subjective information.

  7. http://www.arg-tech.org/analysiswall.

  8. http://side.computing.dundee.ac.uk.

  9. Ethics for all areas of this study were approved through a university ethics procedure.

  10. The programmes used were: Problem families originally aired July 25th 2012 for sessions 1, 2, 3 and 5 and The morality of gambling originally aired March 2nd 2013 for session 4.

  11. Currently, BBC Radio offers a generic online feedback forum for all radio programs.

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Acknowledgments

This research was supported by RCUK Grant EP/G066019/1 “RCUK Hub: Social Inclusion through the Digital Economy”. The authors would like to thank the reviewers, the SiDE Research Group at the University of Dundee for their feedback on early versions of this paper and Christine Morgan, executive producer of the BBC’s Moral Maze, for her support.

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Correspondence to Rolando Medellin-Gasque.

Appendix: Participants’ quotes

Appendix: Participants’ quotes

  1. 1.

    Examples of Unjustified Assertions:

    I think the government viewpoint was simplistic to be honest.

    I think that person is not understanding the situation. It’s almost a middle class view.

  2. 2.

    Example of Argument from Analogy:

    […] It is a trick. Gambling companies trick people. (Assertion) For example, banks were mis-selling private pensions some time ago attracting people with free commissions. How is that different from these people enticing people in to gambling with a 20 pounds free start? It’s a mis-selling of a product. (Justified Assertion with Argument from Analogy)

  3. 3.

    Example of Argument from Position to Know:

    […] You cannot tackle the problem by raising the price of beer, the problem is how people are educated. (Assertion) I was on a train last month where four guys came on and each one had a carrier bag of beer and they started playing cards loudly with money all over the table. If you’d doubled the price of the beer, it would have made no difference for them. For some people is not about the price, it’s about lack of education and consideration (Justified Assertion with Argument from Position to Know).

  4. 4.

    Examples used by participants to agree (sentiment identifiers are in boldface):

    […] I agree with that , what I think is that they’re come now to a more accurate definition in that these are families with five to seven deprivations […]

    […] Precisely , what she just said is the main point in this debate, it’s got individuals in the messes but also got society in to messes as well […]

  5. 5.

    In the following example, Female 1 agrees to an direct question raised by the Researcher:

    Researcher: Do you agree that the figures are important to sustain an argument when you throw in a number like 120,000?

    Female 1: To some extent, you have to accept the numbers that you’re given because I don’t know anything different […]

  6. 6.

    Examples of disagreement used by participants:

    […] No , it would only need a few, half a minute of somebody giving their story about how they got to the state they’re in with gambling. […]

    […] I think it’s not just the poor family who has the moral problems. There is a general lack of - in my opinion, morals in a lot of families, forget about their income status […]

  7. 7.

    Example of Justified Assertion with Disagreement:

    […] we don’t want to tell people what to do (Disagreement) but if you see somebody driving badly, the police will say: you should be driving on the other side of the road. (Argument from Analogy) The trouble is the social work departments have become afraid that if they left a child with the parents, if something happened to that child there would be a big enquiry and they would then be seen as negligent (Justified Assertion). So, the default situation for a social worker is to take the child away. […]

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Medellin-Gasque, R., Reed, C. & Hanson, V.L. Recommendations to support interaction with broadcast debates: a study on older adults’ interaction with The Moral Maze . AI & Soc 31, 109–120 (2016). https://doi.org/10.1007/s00146-014-0578-z

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