WiMo

Mody, Ruturaj N.; Willis, Katharine S.; Kerstein, Roland

doi:10.1145/1658550.1658564

Cited by 37 publications

(14 citation statements)

References 6 publications

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“…Inspired by Nold's work on emotional cartography (Nold 2009) and the rise of the Quantified-Self movement (Li et al 2013), there currently is an increased interest in exploring how mobile, wearable and Quantified-Self technology could potentially be used to capture and collect people's emotional experiences of urban places (Rooksby et al 2014;Matassa 2013;Resch et al 2015;Stals, Smyth, and Mival 2017b;Quercia, Schifanella, and Aiello 2014) and the potential for sharing this personal data with other people using emotion maps (Al-Husain, Kanjo, and Chamberlain 2013; Leahu, Schwenk, and Sengers 2008;Matassa and Rapp 2015;Mody, Willis, and Kerstein 2009;Nold 2004;Nold 2009). Based on social science studies of the concept of place attachment (Manzo 2005;Gustafson 2001; Scannell and Gifford 2010) and these urban HCI studies attempting to leverage people's emotional experience of the urban environment, we argue that places that are meaningful to people on a personal level, could provide a suitable lens for further investigation, as these personally meaningful places are typically the places that a person has a strong emotional bond with (Stals, Smyth, and Mival 2017a).…”

Section: Exploring Emotion and Person-place Relationships In The Urbamentioning

confidence: 99%

“…More recently, emotion maps have been used to visualize stress hotspots in supermarkets (El Mawass and Kanjo 2013), people's feelings in places affected by environmental factors like air pollution, noise and green space (MacKerron and Mourato 2012), people's emotional feelings of different typologies of a places (e.g. restaurants, museums, stores) (Mody, Willis, and Kerstein 2009) and feelings in a place based on personal memories that happened in that place (Matassa and Rapp 2015). From a research perspective, this makes sense.…”

Section: Emotion Mapsmentioning

confidence: 99%

“…Due to the limited insight provided by arousal maps regarding a person's actual emotions connected to places in the urban environment, more recent studies make use of emotion maps based on emotion categories (Mody, Willis, and Kerstein 2009;Matassa and Rapp 2015;Quercia, Schifanella, and Aiello 2014;Resch et al 2016). For example, Matassa and Rapp designed and developed a concept for a smartphone app for cyclists called UMap, which aims to enhance people's reminiscing of past experiences by linking them to the context (i.e.…”

Section: Emotion Maps Based On Emotion Categoriesmentioning

confidence: 99%

“…Emotion maps that do attempt to depict a person's actual emotions connected to a place (i.e. rather than arousal levels), as the one depicted in Figure 3, typically use simplified emotion categories based on qualitative measurements or crowdsourced data, thus limiting the range of emotions on the resulting emotion map (Mody, Willis, and Kerstein 2009;Matassa and Rapp 2015;Quercia, Schifanella, and Aiello 2014;Resch et al 2016). Source: generated by the authors For example, since people can express their emotions quite differently, Mody, Willis and Kerstein developed an "emotional matrix" allowing participants to indicate their emotional response to private public and semi-public places along four axis: Like and Don't Like, Comfortable and Uncomfortable (Mody, Willis, and Kerstein 2009).…”

Section: Emotion Maps Based On Emotion Categoriesmentioning

confidence: 99%

“…rather than arousal levels), as the one depicted in Figure 3, typically use simplified emotion categories based on qualitative measurements or crowdsourced data, thus limiting the range of emotions on the resulting emotion map (Mody, Willis, and Kerstein 2009;Matassa and Rapp 2015;Quercia, Schifanella, and Aiello 2014;Resch et al 2016). Source: generated by the authors For example, since people can express their emotions quite differently, Mody, Willis and Kerstein developed an "emotional matrix" allowing participants to indicate their emotional response to private public and semi-public places along four axis: Like and Don't Like, Comfortable and Uncomfortable (Mody, Willis, and Kerstein 2009). Quercia, Schifanella and Aiello limited the emotion categories for their crowdsourced perceptions of places to Beautiful, Quiet and Happy due to their intended use of the crowdsourced emotion data to create walking routes through the city with those specific characteristics (Quercia, Schifanella, and Aiello 2014).…”

Section: Emotion Maps Based On Emotion Categoriesmentioning

confidence: 99%

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Capturing, Exploring and Sharing People’s Emotional Bond with Places in the City using Emotion Maps

Stals¹,

Smyth²,

Mival³

2018

airea

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With the vision of ubiquitous computing becoming increasingly realized through smart city solutions, the proliferation of smartphones and smartwatches, and the rise of the quantified-self movement, a new technological layer is being added to the urban environment. This technological layer offers the possibility to capture, track, measure, visualize, and augment our experience of the urban environment. But to that end, there is a growing need to better understand the triangular relationship between person, place, and technology. Urban HCI studies are increasingly focusing on emotion and affect to create a better understanding of people’s experience of the city, and to investigate how technology could potentially play a role in augmenting this urban lived experience. Artist Christian Nold for example, used wearable technology to measure people's arousal levels as they walked freely through the urban environment, identifying locations in the city that evoked an emotional response from people. After these walks, people’s arousal levels were superimposed on a map of the city and participants were asked to interpret their own data, resulting in aggregated, fully annotated, and beautifully visualized emotion maps of the city. Based on a systematic review of emotions maps in existing literature, and our own work which seeks to understand how people’s experiences of places in the urban environment that are meaningful to them on a personal level, for example the place where they have met their partner, could potentially inform the design of future technological devices and services, this journal paper discusses the strengths, limitations and potential of capturing, representing, exploring and sharing this personal, geo-located emotion data with other people using emotion maps. Although our analysis seems to indicate that emotion maps in their current form are only of limited efficacy in accurately capturing, representing and communicating the profound, complex emotional bond that people have with personally meaningful places in the city, there appears to be potential for the use of emotion maps as a provocation in a speculative design approach.

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