Kyriaki Kalimeri | Politecnico di Torino (original) (raw)

Papers by Kyriaki Kalimeri

Cornell University - arXiv, Mar 2, 2020

In the age of social media, disasters and epidemics usher not only a devastation and affliction i... more In the age of social media, disasters and epidemics usher not only a devastation and affliction in the physical world, but also prompt a deluge of information, opinions, prognoses and advice to billions of internet users. The coronavirus epidemic of 2019-2020, or COVID-19, is no exception, with the World Health Organization warning of a possible 'infodemic' of fake news. In this study, we examine the alternative narratives around the coronavirus outbreak through advertisements promoted on Facebook, the largest social media platform in the US. Using the new Facebook Ads Library, we discover advertisers from public health and non-profit sectors, alongside those from news media, politics, and business, incorporating coronavirus into their messaging and agenda. We find the virus used in political attacks, donation solicitations, business promotion, stock market advice, and animal rights campaigning. Among these, we find several instances of possible misinformation, ranging from bioweapons conspiracy theories to unverifiable claims by politicians. As we make the dataset available to the community, we hope the advertising domain will become an important part of quality control for public health communication and public discourse in general.

30th Web Conference, WWW 2021, Apr 14, 2021

This paper proposes a sonification model for encoding visual 3D information into sounds, inspired... more This paper proposes a sonification model for encoding visual 3D information into sounds, inspired by the impact properties of the objects encountered during blind navigation. The proposed model is compared against two sonification models developed for orientation and mobility, chosen based on their common technical requirements. An extensive validation of the proposed model is reported; five legally blind and five normally sighted participants evaluated the proposed model as compared to the two competitive models on a simplified experimental navigation scenario. The evaluation addressed not only the accuracy of the responses in terms of psychophysical measurements but also the cognitive load and emotional stress of the participants by means of biophysiological signals and evaluation questionnaires. Results show that the proposed impact sound model adequately conveys the relevant information to the participants with low cognitive load, following a short training session.

Companion Proceedings of The 2019 World Wide Web Conference, 2019

Psychological, political, cultural, and even societal factors are entangled in the reasoning and ... more Psychological, political, cultural, and even societal factors are entangled in the reasoning and decision-making process towards vaccination, rendering vaccine hesitancy a complex issue. Here, administering a series of surveys via a Facebook-hosted application, we study the worldviews of people that "Liked" supportive or vaccine resilient Facebook Pages. In particular, we assess differences in political viewpoints, moral values, personality traits, and general interests, finding that those sceptical about vaccination, appear to trust less the government, are less agreeable, while they are emphasising more on anti-authoritarian values. Exploring the differences in moral narratives as expressed in the linguistic descriptions of the Facebook Pages, we see that pages that defend vaccines prioritise the value of the family while the vaccine hesitancy pages are focusing on the value of freedom. Finally, creating embeddings based on the health-related likes on Facebook Pages, we explore common, latent interests of vaccine-hesitant people, showing a strong preference for natural cures. This exploratory analysis aims at exploring the potentials of a social media platform to act as a sensing tool, providing researchers and policymakers with insights drawn from the digital traces, that can help design communication campaigns that build confidence, based on the values that also appeal to the socio-moral criteria of people.

Demographic Research, 2020

BACKGROUND Social media in scientific research offers a unique digital observatory of human behav... more BACKGROUND Social media in scientific research offers a unique digital observatory of human behaviours and hence great opportunities to conduct research at large scale, answering complex sociodemographic questions. We focus on the identification and assessment of biases in social-media-administered surveys. OBJECTIVE This study aims to shed light on population, self-selection, and behavioural biases, empirically comparing the consistency between self-reported information collected traditionally versus social-media-administered questionnaires, including demographic and psychometric attributes. METHODS We engaged a demographically representative cohort of young adults in Italy (approximately 4,000 participants) in taking a traditionally administered online survey and then, after one year, we invited them to use our ad hoc Facebook application (988 accepted) where they filled in part of the initial survey. We assess the statistically significant differences indicating population, self-selection, and behavioural biases due to the different context in which the questionnaire is administered.

Wireless Communications and Mobile Computing, 2018

Reliable detection of cognitive load would benefit the design of intelligent assistive navigation... more Reliable detection of cognitive load would benefit the design of intelligent assistive navigation aids for the visually impaired (VIP). Ten participants with various degrees of sight loss navigated in unfamiliar indoor and outdoor environments, while their electroencephalogram (EEG) and electrodermal activity (EDA) signals were being recorded. In this study, the cognitive load of the tasks was assessed in real time based on a modification of the well-established event-related (de)synchronization (ERD/ERS) index. We present an in-depth analysis of the environments that mostly challenge people from certain categories of sight loss and we present an automatic classification of the perceived difficulty in each time instance, inferred from their biosignals. Given the limited size of our sample, our findings suggest that there are significant differences across the environments for the various categories of sight loss. Moreover, we exploit cross-modal relations predicting the cognitive lo...

Proceedings of the 18th ACM International Conference on Multimodal Interaction, 2016

This paper presents a multimodal framework for assessing the emotional and cognitive experience o... more This paper presents a multimodal framework for assessing the emotional and cognitive experience of blind and visually impaired people when navigating in unfamiliar indoor environments based on mobile monitoring and fusion of electroencephalography (EEG) and electrodermal activity (EDA) signals. The overall goal is to understand which environmental factors increase stress and cognitive load in order to help design emotionally intelligent mobility technologies that are able to adapt to stressful environments from real-time biosensor data. We propose a model based on a random forest classifier which successfully infers in an automatic way (weighted AUROC 79.3%) the correct environment among five predefined categories expressing generic everyday situations of varying complexity and difficulty, where different levels of stress are likely to occur. Time-locating the most predictive multimodal features that relate to cognitive load and stress, we provide further insights into the relationship of specific biomarkers with the environmental/situational factors that evoked them.

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing, 2012

This paper presents the SocioMetric Badges Corpus, a new corpus for social interaction studies co... more This paper presents the SocioMetric Badges Corpus, a new corpus for social interaction studies collected during a 6 weeks contiguous period in a research institution, monitoring the activity of 53 people. The design of the corpus was inspired by the need to provide researchers and practitioners with: a) raw digital trace data that could be used to directly address the task of investigating, reconstructing and predicting people's actual social behavior in complex organizations; b) information about participants' individual characteristics (e.g., personality traits), along with c) data concerning the general social context (e.g., participants' social networks) and the specific situations they find themselves in.

IEEE Transactions on Affective Computing, 2012

This work investigates the suitability of medium-grained meeting behaviors, namely, speaking time... more This work investigates the suitability of medium-grained meeting behaviors, namely, speaking time and social attention, for automatic classification of the Extraversion personality trait. Experimental results confirm that these behaviors are indeed effective for the automatic detection of Extraversion. The main findings of our study are that: 1) Speaking time and (some forms of) social gaze are effective indicators of Extraversion, 2) classification accuracy is affected by the amount of time for which meeting behavior is observed, 3) independently considering only the attention received by the target from peers is insufficient, and 4) distribution of social attention of peers plays a crucial role.

Proceedings of the 14th ACM international conference on Multimodal interaction, 2012

Proceedings of the 15th ACM on International conference on multimodal interaction, 2013

While our daily activities usually involve interactions with others, the state-of-the-art methods... more While our daily activities usually involve interactions with others, the state-of-the-art methods on activity recognition do not exploit the relationship between social interactions and human activity. This paper addresses the problem of interpreting social activity from human-human interactions captured by mobile sensing networks. Our first goal is to discover different social activities such as chatting with friends from human-human interaction logs and then characterize them by the set of people involved, time and location of the occurring event. Our second goal is to perform automatic labeling of the discovered activities using predefined semantic labels such as coffee breaks, weekly meetings, or random discussions. Our analysis was conducted on interaction networks sensed with Bluetooth and infrared sensors by about fifty subjects who carried sociometric badges over 6 weeks. We show that the proposed system reliably recognized coffee breaks with 99% accuracy, while weekly meetings were recognized with 88% accuracy.

Lecture Notes in Computer Science, 2014

ABSTRACT This work investigates in-depth the communication practices within a workplace to unders... more ABSTRACT This work investigates in-depth the communication practices within a workplace to understand whether workers interact face to face or more indirectly with email. We analysed the interactions to understand how these changes affect our work (productivity, deadlines, interesting task) and our wellbeing (positive and negative affective states),by using a variety of data collection methods (sensors and surveys). Our analysis revealed that overall the email was the most frequent medium of commu- nication, but when taking into account just the communication within working hours (8am to 7pm), that face to face interactions were preffered. Correlation analysis revealed significant relationships between Affective States and Situational Factors while Longitudinal Analysis revealed an impact of communication features and measures of self reported Pro- ductivity and Creativity. These findings lead us to believe that different communication processes (synchronous and asynchronous) can impact Positive and Negative Affective States as well as how productive and creative you feel at work.

Data Mining and Knowledge Discovery

In this paper we modeled the effects that dominant people induce on the nonverbal behavior (speec... more In this paper we modeled the effects that dominant people induce on the nonverbal behavior (speech energy and body motion) of the other meeting participants using Granger causality technique. Our initial hypothesis that more dom-inant people have generalized higher influence has not been validated. However, from the correlational analysis some interesting patterns emerged: contradicting our initial hy-pothesis dominant individuals are not accounting for the majority of the causal flow in a social interaction. More-over, they seem to have more intense causal effects as their causal density was significantly higher. Finally dominant individuals tend to respond to the causal effects more often with complementarity than with mimicry.

Youth unemployment rates are still in alerting levels for many countries, among which Italy. Dire... more Youth unemployment rates are still in alerting levels for many countries, among which Italy. Direct consequences include poverty, social exclusion, and criminal behaviours, while negative impact on the future employability and wage cannot be obscured. In this study, we employ survey data together with social media data, and in particular likes on Facebook Pages, to analyse personality, moral values, but also cultural elements of the young unemployed population in Italy. Our findings show that there are small but significant differences in personality and moral values, with the unemployed males to be less agreeable while females more open to new experiences. At the same time, unemployed have a more collectivist point of view, valuing more in-group loyalty, authority, and purity foundations. Interestingly, topic modelling analysis did not reveal major differences in interests and cultural elements of the unemployed. Utilisation patterns emerged though; the employed seem to use Faceboo...

The COVID-19 pandemic radically changed the lives of millions with unprecedented economic, societ... more The COVID-19 pandemic radically changed the lives of millions with unprecedented economic, societal, but also psychological consequences. Containing the pandemic urged for rapid measures, the success of which hugely rely on mass cooperation. Here, we employed a sentiment (DepechMood++) and a morality (MoralStrenght) dictionary, to analyse user-generated text on the Twitter platform. Quantifying cooperation and competitive attitudes from the linguistic cues during the pandemic, we depict the moral profiles associated with each position. Moreover, we discuss the moral and emotional profiles of individuals who tweeted about conspiracy theories, and the evolution of moral values throughout the pandemic period for four casestudy countries. Our findings show the evolution of moral values during the pandemic for Italy, United States, New Zealand and China. Comparing the moral profiles of cooperative versus competitive attitudes, we find that high loyalty and consideration of the group memb...

Sensors (Basel, Switzerland), 2020

This paper presented the assessment of cognitive load (as an effective real-time index of task di... more This paper presented the assessment of cognitive load (as an effective real-time index of task difficulty) and the level of brain activation during an experiment in which eight visually impaired subjects performed two types of tasks while using the white cane and the Sound of Vision assistive device with three types of sensory input—audio, haptic, and multimodal (audio and haptic simultaneously). The first task was to identify object properties and the second to navigate and avoid obstacles in both the virtual environment and real-world settings. The results showed that the haptic stimuli were less intuitive than the audio ones and that the navigation with the Sound of Vision device increased cognitive load and working memory. Visual cortex asymmetry was lower in the case of multimodal stimulation than in the case of separate stimulation (audio or haptic). There was no correlation between visual cortical activity and the number of collisions during navigation, regardless of the type...

ArXiv, 2019

Social media in scientific research offer a unique digital observatory of human behaviours and he... more Social media in scientific research offer a unique digital observatory of human behaviours and hence great opportunities to conduct research at large scale answering complex sociodemographic questions. We focus on the identification and assessment of biases in social media administered surveys. This study aims to shed light on population, self-selection and behavioural biases, empirically comparing the consistency between self-reported information collected traditionally versus social media administered questionnaires, including demographic and psychometric attributes. We engaged a demographically representative cohort of young adults in Italy (approximately 4,000 participants) in taking a traditionally administered online survey and then, after one year, we invited them to use our ad hoc Facebook application (988 accepted) where they filled in part of the initial survey. We assess the statistically significant differences indicating population, self-selection, and behavioural biase...

PLoS Computational Biology, 2021

Vaccine hesitancy is considered as one of the leading causes for the resurgence of vaccine preven... more Vaccine hesitancy is considered as one of the leading causes for the resurgence of vaccine preventable diseases. A non-negligible minority of parents does not fully adhere to the recommended vaccination schedule, leading their children to be partially immunized and at higher risk of contracting vaccine preventable diseases. Here, we leverage more than one million comments of 201,986 users posted from March 2008 to April 2019 on the public online forum BabyCenter US to learn more about such parents. For 32% with geographic location, we find the number of mapped users for each US state resembling the census population distribution with good agreement. We employ Natural Language Processing to identify 6884 and 10,131 users expressing their intention of following the recommended and alternative vaccination schedule, respectively RSUs and ASUs. From the analysis of their activity on the forum we find that ASUs have distinctly different interests and previous experiences with vaccination ...

Cornell University - arXiv, Mar 2, 2020

30th Web Conference, WWW 2021, Apr 14, 2021

Companion Proceedings of The 2019 World Wide Web Conference, 2019

Demographic Research, 2020

Wireless Communications and Mobile Computing, 2018

Proceedings of the 18th ACM International Conference on Multimodal Interaction, 2016

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing, 2012

IEEE Transactions on Affective Computing, 2012

Proceedings of the 14th ACM international conference on Multimodal interaction, 2012

Proceedings of the 15th ACM on International conference on multimodal interaction, 2013

Lecture Notes in Computer Science, 2014

Data Mining and Knowledge Discovery

Sensors (Basel, Switzerland), 2020

ArXiv, 2019

PLoS Computational Biology, 2021

Proceedings of the 19th International Conference on Digital Audio Effects (DAFx-16), 2016

Lecture Notes in Computer Science, 2016

In this study, we aim to better the user experience of the virtually impaired when navigating in ... more In this study, we aim to better the user experience of the virtually impaired when navigating in unfamiliar outdoor environments assisted by mobility technologies. We propose a framework for assessing their cognitive-emotional experience based on ambulatory monitoring and multimodal fusion of electroencephalography, electrodermal activity , and blood volume pulse signals. The proposed model is based on a random forest classifier which successfully infers in an automatic way the correct urban environment among eight predefined categories (AUROC 93%). Geolocating the most predictive multimodal features that relate to cognitive load and stress, we provide further insights into the relationship of specific biomarkers with the environmental/situational factors that evoked them.