The role of cultural heritage in wellbeing perceptions: a web-based software analysis in two Italian provinces
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DOI:
https://doi.org/10.13138/2039-2362/2724Abstract
In the last decades, the Internet and the Web have given citizens unprecedented possibilities of communication and contents co-creation, which produce a huge amount of data about the places which they live in. The advent of social Web has been recently upsetting patterns of re-territorialization, practices of urban experiences as well as uses of cultural heritage, growingly mediated by ICTs so that an extraordinary repository of online data and e-discourses has been affecting the imageries which territories are built on. As a result, analysing the territories and their tangible and intangible cultural assets through data retrieved from the Web has received considerable attention as a promising method for place-based applied researches focused on several territorial dimensions, ranging from sustainability to wellbeing and heritage. Particularly, this paper aims at critically exploring the role of cultural heritage in influencing the online narratives and perceptions of territorial wellbeing in two Italian provinces selected as case studies. Although the Web data use is not without its challenges, the paper is focused on a multi-method approach encompassing Web data retrieval, selection, classification and analysis, in addition to an exploration based on the Sentiment Analysis approach, aimed at investigating the online “sentiment” about local cultural heritage and its implications in terms of collective wellbeing in two selected Italian provinces. The main goal is to compare narratives about the interplay between cultural heritage and wellbeing in areas included in official rankings of quality of life, based on a set of indicators, with those co-created in the Web in order to provide new theoretical/methodological insights on the challenges and potentialities deriving from the use of web-based sentiment analysis methodologies in territorial research.
Negli ultimi decenni l’avvento del Web sociale ha scompaginato i processi di territorializzazione, le esperienze urbane e le percezioni del patrimonio culturale in modo così pervasivo che la mole sempre più consistente di dati online e narrazioni digitali può influenzare il modo in cui i territori sono percepiti. Di conseguenza, i dati estrapolati dal Web rappresentano una base informativa sempre più largamente usata per l’analisi dei territori e del loro patrimonio culturale tangibile e intangibile. In particolare, questo articolo esplora criticamente il ruolo rivestito dal patrimonio culturale nell’influenzare le narrazioni online e le percezioni del benessere territoriale in due province italiane selezionate come casi di studio. Nonostante alcune limitazioni metodologiche, la ricerca si fonda su un approccio multi-metodo che include l’estrapolazione di dati dal Web, la loro selezione, classificazione e analisi attraverso la metodologia della Sentiment Analysis, finalizzata a cogliere il “sentiment” (opinione) online sul patrimonio culturale locale e sulle sue implicazioni in termini di benessere collettivo. L’obiettivo principale è comparare le percezioni di territori inseriti nelle classifiche sulla qualità della vita sulla base di una serie di indicatori con quelle co-create nel Web al fine di approfondire le nuove prospettive teorico-metodologiche derivanti dall’utilizzo della Sentiment Analysis nelle indagini territoriali.
References
Agryzkov T., Martí P., Tortosa L., Vicent J. F. (2016), Measuring urban activities using Foursquare data and network analysis: A case study of Murcia (Spain), «International Journal of Geographical Information Science», pp. 1-22.
Alaei A. R., Becken S., Stantic B. (2019), Sentiment analysis in tourism: capitalizing on big data, «Journal of Travel Research», 58, 2, pp.175-191.
Albanese V. (2017), Il territorio mediato. Sentiment Analysis Methodology e sua applicazione al Salento; Bologna: Bononia University Press.
Anholt S. (2010), Places: Identity, image and reputation; Houndmills: Palgrave MacMillan.
Antonelli F., Azzi M., Balduini M., Ciuccarelli P., Valle E. D., Larcher R. (2014), City sensing: visualising mobile and social data about a city scale event, Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces, pp.337–338.
Anttiroiko A.V. (2015), City branding as a response to global intercity competition, «Growth and Change», 46, 2, pp.233–252.
Arribas-Bel D. (2014), Accidental, open and everywhere: Emerging data sources for the understanding of cities, «Applied Geography», 49, pp. 45–53.
Arribas-Bel D. (2014), Accidental, open and everywhere: Emerging data sources for the understanding of cities, «Applied Geography», 49, pp.45–53.
Arribas-Bel D., Kourtit K., Nijkamp P. and Steenbruggen J. (2015), Cyber Cities: Social Media as a Tool for Understanding Cities, «Applied Spatial Analysis and Policy», 8, 3, pp.231–247.
Atkinson S. (2013), Beyond components of wellbeing: the effects of relational and situated assemblage, «Topoi», 32, pp.137-44.
Atkinson S., Fuller S., Painter J. (2012), Wellbeing and place; Farnham: Ashgate.
Aubrecht C., Ungar J., Freire S. (2011), Exploring the potential of volunteered geographic information for modeling spatio-temporal characteristics of urban population. A case study for Lisbon Metro using Foursquare check-in data, Proceedings of the 7th International Conference on Virtual Cities and Territory, Lisbon: Nova University of Lisbon, pp. 57–60.
Ballas D. (2013), What makes a ‘happy city’?, «Cities», 32, pp.39-50.
Binkley S. (2011), Happiness, positive psychology and the program of neoliberal governmentality, «Subjectivity», 4, pp.371-94.
Bollen J., Mao H., Pepe A. (2011), Modeling public mood and emotion: Twitter sentiment and socio- economic phenomena, Proceedings of the Fifth International Conference on Weblogs and Social Media, Barcelona, Spain: AAAI Press, pp. 450–453.
Boy J. D., Uitermark J. (2017), Reassembling the city through Instagram, «Transactions of the Institute of British Geographers», 42, pp.612–624.
Braun E., Eshuis J., Klijn E.-H. (2014), The effectiveness of place brand communication, «Cities», 41, pp.64–70.
Bruni L., Porta P.L., a cura di (2006), Economics and Happiness: Framing the Analysis, Oxford: Oxford University Press.
Bruns A., Burgess J. (2011), The use of Twitter hash- tags in the formation of ad hoc publics, Proceedings of the 6th European Consortium for Political Research (ECPR), General Conference, pp. 1-9.
Castells M. (2009), Communication power; Oxford: Oxford University Press.
Ceron A., Curini L., Iacus S. (2014), Social Media e Sentiment Analysis. L’evoluzione dei fenomeni sociali attraverso la Rete; Springer: Milano.
Cerrone D. (2015), A Sense of Place. Exploring the potentials and possible uses of Location Based Social Network Data for urban and transportation planning in Turku City Centre, «Report delivered by MTÜ Spatial Intelligence Unit in collaboration with the Estonian Academy of Arts», retrieved from www.spinunit.eu.
Dave K., Lawrence S., Pennock D.M. (2003), Mining the peanut gallery: opinion extraction and semantic classification of product reviews, International World Wide Web Conference, New York: ACM, pp.519-528.
de Chazal J. A. (2010), Systems approach to livability and sustainability: defining terms and mapping relationships to link desires with ecological opportunities and constraints, «Systems Research and Behavioral Science», 27, pp. 585-597.
Easterlin R., a cura di (2002), Happiness in Economics, United Kingdom: Edward Elgar Publishing Inc.
Ferretti V., Bottero M., Mondini G. (2014), Decision making and cultural heritage: An application of the Multi-Attribute Value Theory for the reuse of historical buildings, «Journal of Cultural Heritage», 15, 16, pp. 644-655.
Fleuret S. (2007), Bien-être, santé et géographie, in Géographie de la santé, un panorama, a cura di S. Fleuret, J.-P. Thouez, Paris: Editions Economica-Anthropos, pp.72–87.
Fleuret S., Atkinson S. (2007), Wellbeing, health and geography: a critical review and research agenda, «The New Zealand Geographer», 63, pp.106-29.
Fleuret S., Prugneau J. (2015), Assessing students’ wellbeing in a spatial dimension. «The Geographical Journal», 181, 2, pp.110-120.
Frey B.S. and Stutzer A. (2002), Happiness and Economics: How the Economy and Institutions Affect Human Well Being, Princeton - New Jersey: Princeton University Press.
Fujiwara D., Cornwall T., Dolan P. (2014), Heritage and Wellbeing, English Heritage: London.
Giffinger R., Haindlmaier G., Kramar H. (2010), The role of rankings in growing city competition, «Urban Research & Practice», 3, 3, pp.299-312, DOI: 10.1080/17535069.2010.524420
Girardin F., Vaccari A., Gerber A., Biderman A., Ratti C. (2009), Quantifying urban attractiveness from the distribution and density of digital footprints, «International Journal of Spatial Data Infrastructures Research» 4, pp.175–200.
Goodchild M. F. (2007), Citizens as sensors: the world of volunteered geography, «GeoJournal», 69, pp.211–221.
Gordon J. (2013), Comparative Geospatial Analysis of Twitter Sentiment Data during the 2008 and 2012 US Presidential Elections; retrieved from https://core.ac.uk/download/pdf/36687937.pdf on September, 16th, 2020.
Graham M. (2015), Contradictory Connectivity: Spatial Imaginaries and Techno-Mediated Positionalities in Kenya’s Outsourcing Sector, «Environment and Planning A», 47, pp.867-883.
Graham M., Hale S. A. and Gaffney D. (2014), Where in the world are you? Geolocation and Language Identification in Twitter, «The Professional Geographer», pp.1–11.
Graziano T. (2017), Citizen e-Participation in Urban Planning: Achievements and Future Challenges in a Mediterranean City, «International Journal of E-Planning Research», 6, 3, pp.1-18, DOI: 10.4018/IJEPR.2017070101.
Graziano T., Albanese V. (2020), Online Place Branding for Natural Heritage: Institutional Strategies and Users’ Perceptions of Mount Etna (Italy), «Heritage», 3, pp.1539-1559, doi:10.3390/heritage3040085.
Greenberg M. (2008), Branding New York: How a city in crisis was sold to the world, New York: Routledge.
Grinberg N., Naaman M., Shaw B., and Lotan G. (2013), Extracting Diurnal Patterns of Real World Activity from Social Media, The International AAAI Conference on Weblogs and Social Media, pp.1–10.
Guzman P.C., Pereira Roders A.R., Colenbrander B.J.F. (2014), Bridging the gap between urban development and cultural heritage protection, IAIA14 Conference Proceedings Impact Assessment for Social and Economic Development 34th Annual Conference of the International Association for Impact Assessment 8 - 11 April 2014.
Hall T., & Hubbard P. (1998), The entrepreneurial city: Geographies of politics, regime and representation, London: John Wiley & Sons.
Hankins K., Powers E. (2009), The disappearance of the state from ‘livable’ urban spaces, «Antipode», 41, pp.845-866.
Harvey D. (1989), From Managerialism to Entrepreneurialism: The Transformation in Urban Governance in Late Capitalism, «Geografiska Annaler», Series B, 71, 1, The Roots of Geographical Change: 1973 to the Present, pp. 3-17.
Hollander J., Graves E., Levanthal T. (2014), Using Big Data to Study Urban Sentiments: Twitter Data vs. Published Meeting Minutes, «Working paper», Tufts University.
Hollander J.B., Renski H. (2015) Measuring Urban Attitudes Using Twitter: An Exploratory Study, Working Paper WP15JH1 2015, Lincoln Institute of Land Policy.
Jessop B., Sum N.-L. (2000), An entrepreneurial city in action: Hong Kong’s emerging strategies in and for (inter)urban competition, «Urban Studies», 37, pp.2287–2313.
Kitchin R. (2013), Big data and human geography: Opportunities, challenges and risks, «Dialogues in Human Geography», 3, 3, pp.262-267.
Korpela K. M. (1989), Place identity as a product of environmental self regulation, «Journal of environmental Psychology», 9, pp.241-256.
Kovacs-Gyori A., Ristea A., Havas C., Resch B., Cabrera-Barona P. (2018), #London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data. «Urban Planning», 3, 1, pp.75–99 DOI: 10.17645/up.v3i1.1287.
Lane R.E. (2000), The Loss of Happiness in Market Economies, New Haven and London: Yale University Press.
Layard R. (2005), Happiness: Lessons from a New Science; New York and London: Penguin.
Lee R., Wakamiya S., K. Sumiya (2013), Urban area characterization based on crowd behavioral lifelogs over Twitter. «Personal and Ubiquitous Computing», 17, 4, pp.605-620.
Liu B. (2006), Web Data Mining; exploring hyperlinks, contents and usage data; New York: Springer.
Mäntylä M. V., Graziotin D., Kuutila M. (2018), The evolution of sentiment analysis—A review of research topics, venues, and top cited papers, «Computer Science Review», 27, pp.16-32.
Martí P., Serrano-Estrada L., Nolasco-Cirugeda A. (2019), Social Media data: Challenges, opportunities and limitations in urban studies, «Computers, Environment and Urban Systems», 74, pp.161-174.
Massey D. (2005), For Space, London: Sage.
Matni, Z. (2015), Using Social Media Data to Measure and Influence Community Well-Being, «Bulletin of IEEE Technical Committee on Digital Libraries», 11, 3
https://bulletin.jcdl.org/Bulletin/v11n3/papers/155-Matni.pdf, retrieved on January, 8th, 2020.
Mitchell L., Frank M. R., Harris K. D., Dodds P. S., and Danforth C. M. (2013), The geography of happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place, «PloS one», 8, 5, pp.44-17.
Nasukawa T., J. Yi (2003), Sentiment analysis: Capturing favorability using natural language processing, The Second International Conferences on Knowledge Capture, New York: ACM, pp.70–77.
Pacione M. (1990), Urban liveability: a review, «Urban Geography», 11, pp.1-30.
Pacione M. (2003), Urban environmental quality and human wellbeing: a social geographical perspective, «Landscape and Urban Planning», 65, pp.19-30.
Pak A., Paroubek P. (2010), Twitter as a corpus for sentiment analysis and opinion mining, Proceedings of the International Conference on Language Resources and Evaluation, pp. 1320–1326.
Pang B., Lee L. (2008), Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval; Boston – Delft: Now.
Paradiso M. (2003), Geography, Planning and the Internet: Introductory Remarks, «Netcom», 17, pp. 129-138.
Power A., Smith K., Heritage, health and place: The legacies of local community-based heritage conservation on social wellbeing, Health & Place, 39, 160-167.
Quercia D., Ellis J., Capra L. and Crowcroft J. (2012), Tracking gross community happiness from tweets, Proceedings of the ACM 2012 conference on Computer Supported, New York: ACM Digital Library, pp. 965-968.
Resch B., Summa A., Zeile P., Strube M. (2016), Citizen-centric urban planning through extracting emotion information from Twitter in an interdisciplinary space-time-linguistics algorithm, «Urban Planning», 1, 2, pp.114–127.
Roberts H., Resch B., Sadler J., Chapman L., Petutschnig A., Zimmer S. (2018), Investigating the Emotional Responses of Individuals to Urban Green Space Using Twitter Data: A Critical Comparison of Three Different Methods of Sentiment Analysis, «Urban Planning», 3, 1, pp. 21-33. DOI: 10.17645/up.v3i1.1231.
Sagl G., Resch B., Hawelka B., Beinat E. (2013), From social sensor data to collective human behaviour patterns–Analysing and visualising spatio-temporal dynamics in urban environments, GI_Forum 2012: Geovizualisation, society and learning, Jekel, T.; Car, A.; Strobl, J.; & Griesebner, G., a cura di, Berlin and Offenbach: Herbert Wichmann Verlag, pp.54-63.
Saker M. and Evans L. (2016), Locative Media and Identity: Accumulative Technologies of the Self, Open: Sage, 6, 3, pp.1–10.
Sánchez-Rada, J., Iglesias C.A. (2019), Social context in sentiment analysis: Formal definition, overview of current trends and framework for comparison, «Information Fusion», 52, pp. 344-356.
Sayer F. (2018) Understanding well-being: A mechanism for measuring the impact of heritage practice on well-being, in Labrador A.M., Silberman N.A. (eds.) The Oxford Handbook of Public Heritage Theory and Practice, Oxford University Press: Oxford, UK, 2018.
Sloan L. (2017), Social science 'Lite'? Deriving demographic proxies from Twitter, in The SAGE Handbook of Social Media Research Methods, a cura di L. Sloan, A. Quan-Haase, London: SAGE, pp. 90-104.
Smith D. M. (1973), The geography of social well-being in the United States: an introduction to territorial social indicators, New York: McGraw-Hill.
Sui D., Goodchild M. (2011), The convergence of GIS and social media: Challenges for GIScience, «International Journal of Geographical Information Science», 25, 11, pp.1737-1748.
Van Kamp I., Leidelmeijer K., Marsman G. and De Hollander A. (2003), Urban environmental quality and human well-being Towards a conceptual framework and demarcation of concepts; a literature study, «Landscape and Urban Planning», 65, pp.5–18.
Yang J., Leskovec J. (2011), Patterns of Temporal Variation in Online Media Categories and Subject Descriptors, «ACM International Conference on Web Search and Data Minig; WSDM», pp.1–13.
Yea L., Björnerb E. (2018), Linking city branding to multi-level urban governance in Chinese mega- cities: A case study of Guangzhou, «Cities», 80, pp.29-37.
Zhang L., Riddhiman G., Dekhil M., Hsu M., Liu B. (2011), Combining lexicon-based and learning-based methods for Twitter sentiment analysis; Palo Alto, CA: HP Laboratories.
