Data Journalism, Millennials & Social Networks

Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos para a obtenção do grau de Mestre em Ciências da Comunicação, ramo de Jornalismo

Social networks and cooperative learning in a MOOC

MOOCs are changing the educational landscape and gaining a lot of attention in scientific literature. However, the pedagogical design of these proposals has been called into question. It is precisely MOOCs’ social aspect, i.e. the interaction between course participants and the support for learning processes that has become one of the main topics of interest. This article presents the results of a research project carried out at the University of the Basque Country, which focused in cooperative learning and the intensive use of social networks in a MOOC. Significant data was compiled through Likert-type surveys, revealing that the use of both external and internal social networks in a massive open online course is a factor that is evaluated positively by students. We argue that the use of social networks as a learning strategy in a MOOC has an influence on academic performance and on the students' success rate. Furthermore, the participants’ age also has a bearing on the social networks they use, and we have found that the younger members tend to work with external networks such as Twitter or personal blogs, whereas the older students are more inclined to use forums from the Chamilo or Ning platforms.

Are they adicctied to college students social networks?

The development of the Internet and in particular of social networks has supposedly given a new view to the different aspects that surround human behavior. It includes those associated with addictions, but specifically the ones that have to do with technologies. Following a correlational descriptive design we present the results of a study, which involved university students from Social and Legal Sciences as participants, about their addiction to the Internet and in particular to social networks. The sample was conformed of 373 participants from the cities of Granada, Sevilla, Málaga, and Córdoba. To gather the data a questionnaire that was design by Young was translated to Spanish. The main research objective was to determine if university students could be considered social network addicts. The most prominent result was that the participants don’t consider themselves to be addicted to the Internet or to social networks; in particular women reflected a major distance from the social networks. It’s important to know that the results differ from those found in the literature review, which opens the question, are the participants in a phase of denial towards the addiction?

Social networks applied to training

In this article, we address the importance and relevance that social networks exhibit in their use as an educational resource.  This relevance relies in the possibility of implementing new learning resources or increasing the level of the participant's connectivity, as well as developing learning communities.  Also, the risk entailed from their use is discussed, especially for the students that have a low technological education or those having excessive confidence on the media.  It is important to highlight that the educational use of social networks is not a simple extension or translation of the student's habitual, recreational use, but that it implies an important change in the roles given to teachers as well as learners; from accommodative learning environments that only encourage memorization to other environments that demand an active, reflective, collaborative and proactive attitude, that require the development/acquisition of technological as well as social abilities, aptitudes and values.  It is also important to highlight that a correct implementation and adequate use will not only foment formal learning, but also informal and non-formal learning.

Identity and Link Reliability in Social Networks

This paper considers a non-cooperative network formation game where identity is introduced as a single dimension to capture the characteristics of a player in the network. Players access to the benefits from the link through direct and indirect connections. We consider cases where cost of link formation paid by the initiator. Each player is allowed to choose their commitment level to their identities. The cost of link formation decreases as the players forming the link share the same identity and higher commitment levels. We then introduce link imperfections to the model. We characterize the Nash networks and we find that the set of Nash networks are either singletons with no links formed or separated blocks or components with mixed blocks or connected.

"Hidden" Social Networks in Behavior Change Interventions

We investigated whether “hidden” (or unobserved) social networks were evident in a 2011 physical activity behavior change intervention in Belfast, Northern Ireland. Results showed evidence of unobserved social networks in the intervention and illustrated how the network evolved over short periods and affected behavior. Behavior change interventions should account for the interaction among participants (i.e., social networks) and how such interactions affect intervention outcome.

CSFinder: A Cold-Start Friend Finder in Large-Scale Social Networks

Recommending users for a new social network user to follow is a topic of interest at present. The existing approaches rely on using various types of information about the new user to determine recommended users who have similar interests to the new user. However, this presents a problem when a new user joins a social network, who is yet to have any interaction on the social network. In this paper we present a particular type of conversational recommendation approach, critiquing-based recommendation, to solve the cold start problem. We present a critiquing-based recommendation system, called CSFinder, to recommend users for a new user to follow. A traditional critiquing-based recommendation system allows a user to critique a feature of a recommended item at a time and gradually leads the user to the target recommendation. However this may require a lengthy recommendation session. CSFinder aims to reduce the session length by taking a case-based reasoning approach. It selects relevant recommendation sessions of past users that match the recommendation session of the current user to shortcut the current recommendation session. It selects relevant recommendation sessions from a case base that contains the successful recommendation sessions of past users. A past recommendation session can be selected if it contains recommended items and critiques that sufficiently overlap with the ones in the current session. Our experimental results show that CSFinder has significantly shorter sessions than the ones of an Incremental Critiquing system, which is a baseline critiquing-based recommendation system.

SocialLDA:Scalable Topic Modeling in Social Networks

Thesis (Master's)--University of Washington, 2012

Adaptive Probabilistic Topic Models for Social Networks

Thesis (Master's)--University of Washington, 2012

Social networks as glocal products: The case of Facebook

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Assessing the role of social networks on migrant labor market outcomes: Evidence from a representative immigrant survey

What role do social networks play in determining migrant labor market outcomes? We examine this question using data from a random sample of 1500 immigrants living in Ireland. We propose a theoretical model formally predicting that immigrants with more contacts have additional access to job offers, and are therefore better able to become employed and choose higher paid jobs. Our empirical analysis confirms these findings, while focusing more generally on the relationship between migrants’ social networks and a variety of labor market outcomes (namely wages, employment, occupational choice and job security), contrary to the literature. We find evidence that having one more contact in the network is associated with an increase of 11pp in the probability of being employed and with an increase of about 100 euros in the average salary. However, our data is not suggestive of a network size effect on occupational choice and job security. Our findings are robust to sample selection and other endogeneity concerns.

Multilevel multitrait-multimethod model: application to the measurement of egocentered social networks

Our goal in this paper is to assess reliability and validity of egocentered network data using multilevel analysis (Muthen, 1989, Hox, 1993) under the multitrait-multimethod approach. The confirmatory factor analysis model for multitrait-multimethod data (Werts & Linn, 1970; Andrews, 1984) is used for our analyses. In this study we reanalyse a part of data of another study (Kogovšek et al., 2002) done on a representative sample of the inhabitants of Ljubljana. The traits used in our article are the name interpreters. We consider egocentered network data as hierarchical; therefore a multilevel analysis is required. We use Muthen's partial maximum likelihood approach, called pseudobalanced solution (Muthen, 1989, 1990, 1994) which produces estimations close to maximum likelihood for large ego sample sizes (Hox & Mass, 2001). Several analyses will be done in order to compare this multilevel analysis to classic methods of analysis such as the ones made in Kogovšek et al. (2002), who analysed the data only at group (ego) level considering averages of all alters within the ego. We show that some of the results obtained by classic methods are biased and that multilevel analysis provides more detailed information that much enriches the interpretation of reliability and validity of hierarchical data. Within and between-ego reliabilities and validities and other related quality measures are defined, computed and interpreted

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 3: Network Theory and Terminology

In this class, we will discuss network theory fundamentals, including concepts such as diameter, distance, clustering coefficient and others. We will also discuss different types of networks, such as scale-free networks, random networks etc. Readings: Graph structure in the Web, A. Broder and R. Kumar and F. Maghoul and P. Raghavan and S. Rajagopalan and R. Stata and A. Tomkins and J. Wiener Computer Networks 33 309--320 (2000) [Web link, Alternative Link] Optional: The Structure and Function of Complex Networks, M.E.J. Newman, SIAM Review 45 167--256 (2003) [Web link] Original course at: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

Social networks and performance in knowledge creation. An application and a methodological proposal

El objetivo de esta tesis es predecir el rendimiento de los estudiantes de doctorado en la Universidad de Girona según características personales (background), actitudinales y de redes sociales de los estudiantes. La población estudiada son estudiantes de tercer y cuarto curso de doctorado y sus directores de tesis doctoral. Para obtener los datos se ha diseño un cuestionario web especificando sus ventajas y teniendo en cuenta algunos problemas tradicionales de no cobertura o no respuesta. El cuestionario web se hizo debido a la complejidad que comportan de las preguntas de red social. El cuestionario electrónico permite, mediante una serie de instrucciones, reducir el tiempo para responder y hacerlo menos cargado. Este cuestionario web, además es auto administrado, lo cual nos permite, según la literatura, unas respuestas mas honestas que cuestionario con encuestador. Se analiza la calidad de las preguntas de red social en cuestionario web para datos egocéntricos. Para eso se calcula la fiabilidad y la validez de este tipo de preguntas, por primera vez a través del modelo Multirasgo Multimétodo (Multitrait Multimethod). Al ser datos egocéntricos, se pueden considerar jerárquicos, y por primera vez se una un modelo Multirasgo Multimétodo Multinivel (multilevel Multitrait Multimethod). Las la fiabilidad y validez se pueden obtener a nivel individual (within group component) o a nivel de grupo (between group component) y se usan para llevar a cabo un meta-análisis con otras universidades europeas para analizar ciertas características de diseño del cuestionario. Estas características analizan si para preguntas de red social hechas en cuestionarios web son más fiables y validas hechas "by questions" o "by alters", si son presentes todas las etiquetas de frecuencia para los ítems o solo la del inicio y final, o si es mejor que el diseño del cuestionario esté en con color o blanco y negro. También se analiza la calidad de la red social en conjunto, en este caso específico son los grupos de investigación de la universidad. Se tratan los problemas de los datos ausentes en las redes completas. Se propone una nueva alternativa a la solución típica de la red egocéntrica o los respondientes proxies. Esta nueva alternativa la hemos nombrado "Nosduocentered Network" (red Nosduocentrada), se basa en dos actores centrales en una red. Estimando modelos de regresión, esta "Nosduocentered network" tiene mas poder predictivo para el rendimiento de los estudiantes de doctorado que la red egocéntrica. Además se corrigen las correlaciones de las variables actitudinales por atenuación debido al pequeño tamaño muestral. Finalmente, se hacen regresiones de los tres tipos de variables (background, actitudinales y de red social) y luego se combinan para analizar cual para predice mejor el rendimiento (según publicaciones académicas) de los estudiantes de doctorado. Los resultados nos llevan a predecir el rendimiento académico de los estudiantes de doctorado depende de variables personales (background) i actitudinales. Asimismo, se comparan los resultados obtenidos con otros estudios publicados.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.