Co-creation in hospitality industry: a case study on the drivers of traveler-generated content

User-generated content in travel industry is the phenomenon studied in this research, which aims to fill the literature gap on the drivers to write reviews on TripAdvisor. The object of study is relevant from a managerial standpoint since the motivators that drive users to co-create can shape strategies and be turned into external leverages that generate value for brands through content production. From an academic perspective, the goal is to enhance literature on the field, and fill a gap on adherence of local culture to UGC given industry structure specificities. The business’ impact of UGC is supported by the fact that it increases e-commerce conversion rates since research undertaken by Ye, Law, Gu and Chen (2009) states each 10% in traveler review ratings boosts online booking in more than 5%. The literature review builds a theoretical framework on required concepts to support the TripAdvisor case study methodology. Quantitative and qualitative data compound the methodological approach through literature review, desk research, executive interview, and user survey which are analyzed under factor and cluster analysis to group users with similar drivers towards UGC. Additionally, cultural and country-specific aspects impact user behavior. Since hospitality industry in Brazil is concentrated on long tail – 92% of hotels in Brazil are independent ones (Jones Lang LaSalle, 2015, p. 7) – and lesser known hotels take better advantage of reviews – according to Luca (2011) each one Yelp-star increase in rating, increases in 9% independent restaurant revenue whereas in chain restaurants the reviews have no effect – , this dissertation sought to understand UGC in the context of travelers from São Paulo (Brazil) and adopted the case of TripAdvisor to describe what are the incentives that drives user’s co-creation among targeted travelers. It has an outcome of 4 different clusters with different drivers for UGC that enables to design marketing strategies, and it also concludes there’s a big potential to convert current content consumers into producers, the remaining importance of friends and family referrals and the role played by incentives. Among the conclusions, this study lead us to an exploration of positive feedback and network effect concepts, a reinforcement of the UGC relevance for long tail hotels, the interdependence across content production, consumption and participation; and the role played by technology allied with behavioral analysis to take effective decisions. The adherence of UGC to hospitality industry, also outlines the formulation of the concept present in the dissertation title of “Traveler-Generated Content”.

Impacto das tecnologias digitais nas bibliotecas universitárias: reflexões sobre o tema

MOREIRA, Luciana Moreira; SILVA, Armando Malheiro da. Impacto das tecnologias digitais nas bibliotecas universitarias: reflexões sobre o tema. Informaçao e sociedade: estudos. Joao Pessoa, v.19, n.3, p. 125-132,2009.

O julgamento sociomoral de universitários usuários de maconha

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A interação do usuário com catálogos bibliográficos on-line: investigação a partir da Teoria Fundamentada

Pós-graduação em Ciência da Informação - FFC

Gamificação aplicada à produção de roteiro para audiovisual educativo interativo

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Gamificação: modelagem de conteúdos para programas e aplicativos educativos no ambiente da TV digital interativa

With the deployment of Digital TV in Brazil, there is a need to foment the development and production of interactive audiovisual quality content, especially for programs that present educational messages from the entertainment concept - defined as Edutertainment. The objective of this study is to propose application of the gamification as a link of communication to encourage and modify user behavior, through a narrative that encourages intrinsic motivation for learning and entertainment in this media. This paper points out that there are few models of screenplays for applications production, particularly educational, with simultaneous interactive applications for television flow or complementary programming content offered. For this reason, a special attention is given to the screenplay, by virtue of inserting in its construction, the elements that make up the mechanics and dynamics of games. As a result, is shown the entry "Gamification-iDTV", which defines these two scenarios, as well as the development of a modeling methodology of a content and process, supported by conceptual maps, wireframes and roadmaps, substantiating the conception and elaboration of screenplay's prototype with elements of gamification for educational programs and its interaction applications.

Aplicação da tecnologia 4G em projetos de telefonia

This paper presents a study based on bibliographic research on LTE technology, chosen for the fourth generation of mobile phones, and the current status of implementation of 4G network in Brazil. The change in user behavior, which now uses data over the voice services, requires transmission networks to be increasingly robust and fast to enable the viewing of videos and use of other platforms that require internet connection. The retrospective of the development of mobile technologies, from 1G up to 4G that is currently used, shows the long road until it came to appliances and how the phone is used nowadays. Finally, the popularity of smartphones and hence the growing number of people with access to 4G networks, demanded new researchs for the development of future generations technologies in order to achieve the demand for speed enabling significant changes in user experience

Revealing the Copy and Paste Habits of End Users

Transferring data across applications is a common end user task, and copying and pasting via the clipboard lets users do so relatively easily. Using the clipboard, however, can also introduce inefficiencies and errors in user tasks. To help researchers and tool developers understand and address these problems, we studied how end users interact with the clipboard through cut, copy, and paste actions. This study was performed by logging clipboard interactions while end users performed everyday tasks. From the clipboard usage data, we have identified several usage patterns that describe how data is transferred within the desktop environment. Such patterns help us understand end user behavior and indicate areas in which clipboard support tools can be improved.

Aplicação da tecnologia 4G em projetos de telefonia

This paper presents a study based on bibliographic research on LTE technology, chosen for the fourth generation of mobile phones, and the current status of implementation of 4G network in Brazil. The change in user behavior, which now uses data over the voice services, requires transmission networks to be increasingly robust and fast to enable the viewing of videos and use of other platforms that require internet connection. The retrospective of the development of mobile technologies, from 1G up to 4G that is currently used, shows the long road until it came to appliances and how the phone is used nowadays. Finally, the popularity of smartphones and hence the growing number of people with access to 4G networks, demanded new researchs for the development of future generations technologies in order to achieve the demand for speed enabling significant changes in user experience

Comparison of 2D and 3D GUI Widgets for Stereoscopic Multitouch Setups

Recent developments in the area of interactive entertainment have suggested to combine stereoscopic visualization with multi-touch displays, which has the potential to open up new vistas for natural interaction with interactive three-dimensional (3D) applications. However, the question arises how the user interfaces for system control in such 3D setups should be designed in order to provide an effective user experience. In this article we introduce 3D GUI widgets for interaction with stereoscopic touch displays. The design of the widgets was inspired to skeuomorphism and affordances in such a way that the user should be able to operate the virtual objects in the same way as their real-world equivalents. We evaluate the developed widgets and compared them with their 2D counterparts in the scope of an example application in order to analyze the usability of and user behavior with the widgets. The results reveal differences in user behavior with and without stereoscopic display during touch interaction, and show that the developed 2D as well as 3D GUI widgets can be used effectively in different applications.

Cognition or Affect? - Exploring Information Processing on Facebook

Recognizing the increasing amount of information shared on Social Networking Sites (SNS), in this study we aim to explore the information processing strategies of users on Facebook. Specifically, we aim to investigate the impact of various factors on user attitudes towards the posts on their Newsfeed. To collect the data, we program a Facebook application that allows users to evaluate posts in real time. Applying Structural Equation Modeling to a sample of 857 observations we find that it is mostly the affective attitude that shapes user behavior on the network. This attitude, in turn, is mainly determined by the communication intensity between users, overriding comprehensibility of the post and almost neglecting post length and user posting frequency.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

Understanding heterogeneity in post-implementation enterprise system usage: towards a fit/misfit-experience-outcome typology

The overarching objective of this dissertation is to uncover why and how individually experienced fits and misfits translate into different outcomes of user behavior and satisfaction and whether these individual fit/misfit outcomes are in line with organizational intent. In search of patterns and possible archetype users in the context of ES PIPs, this dissertation is the first study that specifically links the theoretical concepts of the aggregated individual fit experiences with the individual and organizational outcome of these experiences (i.e. behavioral reaction, user satisfaction, and alignment with organizational intent). The case study’s findings provide preliminary support for four archetype users characterized by specific fit/misfit experience-outcome patterns.

Business model with discount incentive in a P2P-cloud multimedia streaming system

Today P2P faces two important challenges: design of mechanisms to encourage users' collaboration in multimedia live streaming services; design of reliable algorithms with QoS provision, to encourage the multimedia providers employ the P2P topology in commercial live streaming systems. We believe that these two challenges are tightly-related and there is much to be done with respect. This paper analyzes the effect of user behavior in a multi-tree P2P overlay and describes a business model based on monetary discount as incentive in a P2P-Cloud multimedia streaming system. We believe a discount model can boost up users' cooperation and loyalty and enhance the overall system integrity and performance. Moreover the model bounds the constraints for a provider's revenue and cost if the P2P system is leveraged on a cloud infrastructure. Our case study shows that a streaming system provider can establish or adapt his business model by applying the described bounds to achieve a good discount-revenue trade-off and promote the system to the users.

Análisis y modelización de la dinámica emergente durante el proceso de difusión de información en las redes sociales de internet

Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.