47,847 research outputs found
A model for providing emotion awareness and feedback using fuzzy logic in online learning
Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.Peer ReviewedPostprint (author's final draft
Happiness is assortative in online social networks
Social networks tend to disproportionally favor connections between
individuals with either similar or dissimilar characteristics. This propensity,
referred to as assortative mixing or homophily, is expressed as the correlation
between attribute values of nearest neighbour vertices in a graph. Recent
results indicate that beyond demographic features such as age, sex and race,
even psychological states such as "loneliness" can be assortative in a social
network. In spite of the increasing societal importance of online social
networks it is unknown whether assortative mixing of psychological states takes
place in situations where social ties are mediated solely by online networking
services in the absence of physical contact. Here, we show that general
happiness or Subjective Well-Being (SWB) of Twitter users, as measured from a 6
month record of their individual tweets, is indeed assortative across the
Twitter social network. To our knowledge this is the first result that shows
assortative mixing in online networks at the level of SWB. Our results imply
that online social networks may be equally subject to the social mechanisms
that cause assortative mixing in real social networks and that such assortative
mixing takes place at the level of SWB. Given the increasing prevalence of
online social networks, their propensity to connect users with similar levels
of SWB may be an important instrument in better understanding how both positive
and negative sentiments spread through online social ties. Future research may
focus on how event-specific mood states can propagate and influence user
behavior in "real life".Comment: 17 pages, 9 figure
El reto de vincular reputaciĂłn online de destinos turĂsticos con competitividad
The aim of this study is to evidence how 2.0 conversations in social media impact the reputation of destinations. Additionally, the influence of co-creation practices is analysed. The five most competitive destinations worldwide have been chosen for the research. This paper demonstrates that monitoring social media is a challenge in tourism and is a strategic tool to support process decision making and for destination brand building in a sustainable way. Currently, there are several monitoring and analytic tools, but there is a lack of models to systematise and harness it for the Destination Management Organization (DMOs). In conclusion, how tourists play the main role in the competitiveness of Destinations with their experiences and opinions are considered, along with some keys for successful management of social media are given in the view of the results.info:eu-repo/semantics/publishedVersio
Social networks, happiness and health: from sentiment analysis to a multidimensional indicator of subjective well-being
This paper applies a novel technique of opinion analysis over social media
data with the aim of proposing a new indicator of perceived and subjective
well-being. This new index, namely SWBI, examines several dimension of
individual and social life. The indicator has been compared to some other
existing indexes of well-being and health conditions in Italy: the BES
(Benessere Equo Sostenibile), the incidence rate of influenza and the abundance
of PM10 in urban environments. SWBI is a daily measure available at province
level. BES data, currently available only for 2013 and 2014, are annual and
available at regional level. Flu data are weekly and distributed as regional
data and PM10 are collected daily for different cities. Due to the fact that
the time scale and space granularity of the different indexes varies, we apply
a novel statistical technique to discover nowcasting features and the classical
latent analysis to study the relationships among them. A preliminary analysis
suggest that the environmental and health conditions anticipate several
dimensions of the perception of well-being as measured by SWBI. Moreover, the
set of indicators included in the BES represent a latent dimension of
well-being which shares similarities with the latent dimension represented by
SWBI.Comment: 26 pages, 5 figur
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