5 research outputs found
#Santiago is not #Chile, or is it? A Model to Normalize Social Media Impact
Online social networks are known to be demographically biased. Currently
there are questions about what degree of representativity of the physical
population they have, and how population biases impact user-generated content.
In this paper we focus on centralism, a problem affecting Chile. Assuming that
local differences exist in a country, in terms of vocabulary, we built a
methodology based on the vector space model to find distinctive content from
different locations, and use it to create classifiers to predict whether the
content of a micro-post is related to a particular location, having in mind a
geographically diverse selection of micro-posts. We evaluate them in a case
study where we analyze the virtual population of Chile that participated in the
Twitter social network during an event of national relevance: the municipal
(local governments) elections held in 2012. We observe that the participating
virtual population is spatially representative of the physical population,
implying that there is centralism in Twitter. Our classifiers out-perform a non
geographically-diverse baseline at the regional level, and have the same
accuracy at a provincial level. However, our approach makes assumptions that
need to be tested in multi-thematic and more general datasets. We leave this
for future work.Comment: Accepted in ChileCHI 2013, I Chilean Conference on Human-Computer
Interactio
Balancing diversity to counter-measure geographical centralization in microblogging platforms
We study whether geographical centralization is reflected in the virtual population of microblogging platforms. A consequence of centralization is the decreased visibility and findability of content from less central locations. We propose to counteract geographical centralization in microblogging timelines by promoting geographical diversity through: 1) a characterization of imbalance in location interaction centralization over a graph of geographical interactions from user generated content; 2) geolocation of microposts using imbalance-aware content features in text classifiers, and evaluation of those classifiers according to their diversity and accuracy; 3) definition of a two-step information filtering algorithm to ensure diversity in summary timelines of events. We study our proposal through an analysis of a datase
Biased behavior in web activities: from understanding to unbiased visual exploration
Las tendencias actuales en la Web apuntan hacia la personalizaci贸n de contenido, lo que no ser铆a un
problema en un mundo uniforme y sin sesgos, pero nuestro mundo no es ni uniforme ni libre de
sesgos. En esta tesis planteamos la hip贸tesis de que los sesgos sist茅micos y cognitivos que afectan a
las personas en el mundo f铆sico tambi茅n afectan el comportamiento de 茅stas al explorar contenido en
la Web. Proponemos que es posible fomentar una disminuci贸n en el comportamiento sesgado a
trav茅s de una mirada hol铆stica que incluye cuantificaci贸n de sesgos, formulaci贸n de algoritmos, y
dise帽o de interfaces de usuario. Estas tres partes del proceso propuesto son implementadas
utilizando t茅cnicas de Miner铆a de la Web. A su vez, son guiadas por las Ciencias Sociales, y
presentadas a trav茅s de sistemas Casuales de Visualizaci贸n de Informaci贸n. Seguimos un enfoque
transversal en el cual se aplica este proceso con diferentes niveles de profundidad a lo largo de tres
casos de estudio en Wikipedia y Twitter.
Como resultado, observamos que los sesgos presentes en el mundo f铆sico efectivamente se ven
reflejados en plataformas Web, afectando el contenido, la percepci贸n y el comportamiento de las
personas.
A trav茅s del an谩lisis transversal de los casos de estudio, se presentan las siguientes conclusiones:
1) las herramientas de Miner铆a de la Web son efectivas para medir y detectar comportamiento
sesgado;
2) las t茅cnicas de Visualizaci贸n de Informaci贸n enfocadas en personas no expertas fomentan el
comportamiento no sesgado;
y 3) no existen soluciones universales, y en adici贸n a los contextos sociales y culturales, los sesgos
deben ser considerados a la hora de dise帽ar sistemas.
Para alcanzar estas conclusiones se implementaron sistemas "en la selva", evaluados de manera
cuantitativa en un entorno no controlado, con un enfoque en m茅tricas de participaci贸n y
compromiso. El uso de dichas m茅tricas es una contribuci贸n de la tesis, ya que probaron ser efectivas
al medir diferencias en el comportamiento en sistemas exploratorios