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Gastrophysics
  • ISSN: 2056-6522
  • E-ISSN: 2056-6530

Abstract

How a food, or a dish, is named and how its components and attributes are described can all influence the perception and the enjoyment of the food. Therefore, tracing patterns in food descriptions and determining their role can be of value. The aims of this study were the following: (1) to describe the multisensory food experience as represented in microblog entries concerning food and drink on Twitter, (2) to provide an overview of the changes in the above-mentioned food representations during the period 2011–20, and (3) to contribute to a broader understanding of the human–food relationship as reflected on social media – in this case Twitter – and outline its potential utility for the research field of gastrophysics. The combinations of various multisensory attributes co-occurring in a tweet (which we term ‘collocations’) found in the Twitter corpus were examined through the categories of texture, colour, taste, smell/odour, shape and sound. We mapped the collocations of the 20–25 most frequently mentioned food items and their multisensory experience pairings over time. Such time-based knowledge led to a better understanding of the multisensory experience triggers as reflected on Twitter. By analysing the multisensory experience’s frequency of occurrence, we could conclude that the category of colour is the dominant one, while textural, olfactory and auditory collocations with food are rare. In most of the cases, food tweets appear to render a food experience ‘tasty’, ‘good’ and ‘interesting’.

This article is Open Access under the terms of the Creative Commons Attribution 4.0 International licence (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. The CC BY licence permits commercial and noncommercial reuse. To view a copy of the licence, visit https://creativecommons.org/licenses/by/4.0/
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2021-10-01
2024-10-11
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References

  1. Arshamian, A.,, Manko, P., and Majid, A.. ( 2020;), ‘ Limitations in odour simulation may originate from different sensory embodiment. ’, Philosophical Transactions of the Royal Society B: Biological Sciences, 375:1800, n.pag.
    [Google Scholar]
  2. Bakhshi, S.,, Kanuparthy, P., and Gilbert, E.. ( 2014;), ‘ Demographics, weather and online reviews: A study of restaurant recommendations by WWW 2014. ’, Proceedings of the 23rd International Conference on World Wide Web, Seoul, South Korea, April 7–11, New York:: Association for Computing Machinery;, pp. 443454.
    [Google Scholar]
  3. Bujisic, M.,, Bogicevic, V.,, Parsa, H. G.,, Jovanovic, V., and Sukhu, A.. ( 2019;), ‘ It’s raining complaints! How weather factors drive consumer comments and word-of-mouth. ’, Journal of Hospitality & Tourism Research, 43:5, pp. 65681.
    [Google Scholar]
  4. Caliskan, A.,, Bryson, J. J., and Narayanan, A.. ( 2017;), ‘ Semantics derived automatically from language corpora contain human-like biases. ’, Science, 356:6334, pp. 18386.
    [Google Scholar]
  5. Central Statistical Bureau of Latvia ( 2020;), ‘ Over the ten years availability of Internet at households has risen by 30%. ’, 2 November, https://www.csb.gov.lv/en/statistics/statistics-by-theme/science-ict/computers-internet/search-in-theme/2775-internet-usage-habits-latvian. Accessed 15 August 2021.
  6. Crisinel, A.-S., and Spence, C.. ( 2010;), ‘ A sweet sound? Food names reveal implicit associations between taste and pitch. ’, Perception, 39:3, pp. 41725.
    [Google Scholar]
  7. Croijmans, I.,, Hendrickx, I.,, Lefever, E.,, Majid, A., and Van den Bosch, A.. ( 2020;), ‘ Uncovering the language of wine experts. ’, Natural Language Engineering, 26:5, pp. 51130, https://doi.org/10.1017/S1351324919000500. Accessed 23 August 2021.
    [Google Scholar]
  8. Cruse, A.. ( 2006), A Glossary of Semantics and Pragmatics, Edinburgh:: Edinburgh University Press;.
    [Google Scholar]
  9. Deksne, D.. ( 2013;), ‘ Finite state morphology tool for Latvian. ’, Proceedings of the 11th International Conference on Finite State Methods and Natural Language Processing, St Andrews, Scotland, 16–17 July, Stroudsburg, PA:: Association for Computational Linguistics;, pp. 4953.
    [Google Scholar]
  10. Favalli, S.,, Skov, T.,, Spence, C., and Byrne, D. V.. ( 2013;), ‘ Do you say it like you eat it? The sound symbolism of food names and its role in the multisensory product experience. ’, Food Research International, 54:1, pp. 76071.
    [Google Scholar]
  11. Fellows, P.. ( 2017), Food Processing Technology: Principles and Practice, Cambridge:: Woodhead Publishing;.
    [Google Scholar]
  12. Fenko, A.,, Otten, J. J., and Schifferstein, H. N.. ( 2010;), ‘ Describing product experience in different languages: The role of sensory modalities. ’, Journal of Pragmatics, 42:12, pp. 331427.
    [Google Scholar]
  13. Koehn, P.,, Hoang, H.,, Birch, A.,, Callison-Burch, C.,, Federico, M.,, Bertoldi, N.,, Cowan, B.,, Shen, W.,, Moran, C.,, Zens, R., and Dyer, C.. ( 2007;), ‘ Moses: Open source toolkit for statistical machine translation. ’, in A. Zaenen, and A. van den Bosch. (eds), Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions, Prague, Czech Republic, 23–26 June, Stroudsburg, PA:: Association for Computational Linguistics;, pp. 17780.
    [Google Scholar]
  14. Kumar, R.,, and Chambers IV, E.. ( 2019;), ‘ Understanding the terminology for snack foods and their texture by consumers in four languages: A qualitative study. ’, Foods, 8:10, p. 464.
    [Google Scholar]
  15. Mai, R., and Hoffmann, S.. ( 2015;), ‘ How to combat the unhealthy = tasty intuition: The influencing role of health consciousness. ’, Journal of Public Policy & Marketing, 34:1, pp. 6383.
    [Google Scholar]
  16. Mai, R.,, Hoffmann, S.,, Helmert, J. R.,, Velichkovsky, B. M.,, Zahn, S.,, Jaros, D.,, Schwarz, P. E. H., and Rohm, H.. ( 2011;), ‘ Implicit food associations as obstacles to healthy nutrition: The need for further research. ’, The British Journal of Diabetes & Vascular Disease, 11:4, pp. 18286.
    [Google Scholar]
  17. Mairita (@mairitagurova) ( 2020;), ‘ Šodien tējas diena. Kāda ir jūsu mīļākā tēja vai tējas dzeršanas ieradumi? Es pārsvarā dzeru zaļo tēju, ja dzeru melno, tad ar pienu, tēju maisiņos izvēlos tikai tad, ja nav citu variantu. https://t.co/8IRU8fPUko. ’, 21 April, https://twitter.com/mairitagurova/status/1252629364812001281. Accessed 15 August 2021.
  18. Majid, A.. ( 2015;), ‘ Cultural factors shape olfactory language. ’, Trends in Cognitive Sciences, 19:11, p. 11.
    [Google Scholar]
  19. Majid, A.. ( 2021;), ‘ Human olfaction at the intersection of language, culture, and biology. ’, Trends in Cognitive Sciences, 25:2, pp. 11123, https://doi.org/10.1016/j.tics.2020.11.005. Accessed 23 August 2021.
    [Google Scholar]
  20. Majid, A.,, Burenhult, N.,, Sensmyr, M.,, de Valk, J., and Hansson, B. S.. ( 2017;), ‘ Olfactory language and abstraction across cultures. ’, Philosophical Transactions of the Royal Society B, 373:1752, n.pag.
    [Google Scholar]
  21. Min, W.,, Jiang, S., and Jain, R.. ( 2019b;), ‘ Food recommendation: Framework, existing solutions and challenges. ’, IEEE Transactions on Multimedia, 20:10, p. 1.
    [Google Scholar]
  22. Min, W.,, Jiang, S.,, Liu, L.,, Rui. Y., and Jain, R.. ( 2019a;), ‘ A survey on food computing. ’, ACM Computing Surveys (CSUR), 52:5, pp. 136.
    [Google Scholar]
  23. Ngo, M. K., and Spence, C.. ( 2011;), ‘ Assessing the shapes and speech sounds that consumers associate with different kinds of chocolate. ’, Journal of Sensory Studies, 26:6, pp. 42128.
    [Google Scholar]
  24. Puerta, P.,, Laguna, L.,, Vidal, L.,, Ares, G.,, Fiszman, S., and Tárrega, A.. ( 2020;), ‘ Co-occurrence networks of Twitter content after manual or automatic processing: A case-study on “gluten-free”. ’, Food Quality and Preference, 86, n.pag., https://doi.org/10.1016/j.foodqual.2020.103993. Accessed 4 July 2021.
    [Google Scholar]
  25. Spence, C.. ( 2015a;), ‘ Just how much of what we taste derives from the sense of smell?. ’, Flavour, 4, p. 30.
    [Google Scholar]
  26. Spence, C.. ( 2015b;), ‘ Eating with our ears: Assessing the importance of the sounds of consumption to our perception and enjoyment of multisensory flavour experiences. ’, Flavour, 4:3, n.pag.
    [Google Scholar]
  27. Spence, C.. ( 2015c;), ‘ Visual contributions to taste and flavour perception. ’, in M. J. Scotter. (ed.), Food Science, Technology and Nutrition, Colour Additives for Foods and Beverages, Oxford:: University of Oxford;, 7, pp. 189210.
    [Google Scholar]
  28. Spence C.. ( 2017a), Gastrophysics: The New Science of EATING, London:: Penguin Random House;.
    [Google Scholar]
  29. Spence, C.. ( 2017b;), ‘ Breakfast: The most important meal of the day?. ’, International Journal of Gastronomy and Food Science, 8, pp. 16, http://dx.doi.org/10.1016/j.ijgfs.2017.01.003. Accessed 23 August 2021.
    [Google Scholar]
  30. Spence, C.. ( 2021a;), ‘ Explaining seasonal patterns of food consumption. ’, International Journal of Gastronomy & Food Science, 24, n.pag., https://doi.org/10.1016/j.ijgfs.2021.100332. Accessed 23 August 2021.
    [Google Scholar]
  31. Spence, C.. ( 2021b;), ‘ Explaining diurnal patterns of food consumption. ’, Food Quality & Preference, 91, n.pag., https://authors.elsevier.com/sd/article/S0950-3293(21)00025-2. Accessed 23 August 2021.
    [Google Scholar]
  32. Sproģis, U., and Rikters, M.. ( 2020;), ‘ What can we learn from almost a decade of food tweets. ’, in A. Utka,, J. Vaičenonienė,, J. Kovalevskaitė, and D. Kalinauskaitė. (eds), Proceedings of the Ninth International Conference Baltic Human Language Technologies: The Baltic Perspective 2020, Kaunas, Lithuania, 22–23 September, Amsterdam:: IOS Press;, pp. 19198.
    [Google Scholar]
  33. Szczesniak, A. S.. ( 1963;), ‘ Classification of textural characteristics. ’, Journal of Food Science, 28:4, pp. 38589.
    [Google Scholar]
  34. Twitter Developer Platform ( n.d.a;), ‘ Consuming streaming data. ’, https://developer.twitter.com/en/docs/tutorials/consuming-streaming-data. Accessed 15 August 2021.
  35. Twitter Developer Platform ( n.d.b;), ‘ Tools and guides to support your work. ’, https://developer.twitter.com/en/solutions/academic-research/resources. Accessed 15 August 2021.
  36. Velasco, C., and Obrist, M.. ( 2020), Multisensory Experiences, Oxford:: Oxford University Press;.
    [Google Scholar]
  37. Velasco, C.,, Woods, A. T.,, Deroy, O., and Spence, C.. ( 2015;), ‘ Hedonic mediation of the crossmodal correspondence between taste and shape. ’, Food Quality and Preference, 41, pp. 15158.
    [Google Scholar]
  38. Ventura, A. K., and Mennella, J. A.. ( 2011;), ‘ Innate and learned preferences for sweet taste during childhood. ’, Current Opinion in Clinical Nutrition & Metabolic Care, 14:4, pp. 37984.
    [Google Scholar]
  39. Wang, Q. J.,, Mielby, L. A.,, Junge, J. Y.,, Sjoerup Bertelsen, A.,, Kidmose, U.,, Spence, C., and Byrne, D. V.. ( 2019;), ‘ The role of intrinsic and extrinsic sensory factors in sweetness perception of food and beverages: A review. ’, Foods, 8:6, p. 211, https://doi.org/10.3390/foods8060211. Accessed 23 August 2021.
    [Google Scholar]
  40. Kāle, Maija,, Rikters, Matīss, and Šķilters, Jurģis. ( 2021;), ‘ Tracing multisensory food experiences on Twitter. ’, International Journal of Food Design, 6:2, pp. 181212, https://doi.org/10.1386/ijfd_00030_1
    [Google Scholar]
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