990 resultados para Behavioral patterns


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The black-tufted-marmoset (Callithrix penicillata), abundant in the southeastern state of São Paulo, is an exotic and invasive species . The present study aimed to study the behavior and make monitoring a population black-tufted-marmoset in man-made environment. The observations were made following the method of scan sampling, which consists of continuous observations with a duration of three minutes with a fifteen-minute intervals between one record and another. The individuals are monitored at two locations on campus, where two groups were identified (with a mean of 3.50 ± 2.06 individuals) totaling 291 hours and 30 minutes of observation. Were determined tree layers used, and observed that the group of EC preferably utilizes the highest stratum, while the group of LCF uses the middle and lower strata. Types of vocalization, such as calling, interaction and alert and frequency and percentage of these were also observed. The food items consumed by the groups that are similar in the two study sites, mostly sap and leaves were diagnosed. From observations of behavioral patterns was possible to construct an ethogram of the species ' Luiz de Queiroz ' campus, comprising the behaviors of vocalization, locomotion, foraging, game, among others. The results may be useful for development of management techniques and for subsequent studies

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This monograph discuss the postmodernity social reality issues, emphasizing cultural, communicational, technological and informational extents. Via data collection through specific literature, and sources of different medias( internet, books, comic books, movies, novels, sociological, informational, technological, communicational and humanistic theories) behavioral patterns could be analyzed and the postmodern technological,informational and communicational reality as well, and how they mutually influence the “digital culture” construction (also called cyberculture). The results of this research were used to build a narrative which suits the new culture in development both in shape and in content: the scrip “Hotel Seol”. Therefore, “Hotel Seol” is consisted of an interactive and hypermedia narrative, in which the main reference sources are the study mentioned above, cyberpunk science fiction genre and “Hell”-first part of the book “Divine Comedy”, by DanteAlighieri

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Currently zoos and management centers are valuable tools in the maintenance and study of various species. Studies of behavior of captive animals contribute to the improvement of management techniques and the well - being of themselves, encouraging captive breeding and reintroduction also to the natural environment . One of the ways to increase the levels of well-being is the use of environmental enrichment techniques that provide necessary incentives for the welfare of both physical and psychological captive animal . The aim of this study was to identify the types, frequencies and intensities of behavior displayed by three individuals of the species Galictis cuja, belonging to the family Mustelidae and popularly known as lesser grisson , which are captives in municipal zoo in Piracicaba , SP . In addition to evaluating the influence of environmental enrichment techniques on these behavioral parameters. The animals had their behaviors recorded in ethograms through the focal sampling method , 40 hours per person , totaling 120 hours of observation . Were introduced four environmental enrichment techniques related to physical environment, nutrition , perception and cognitive stimulation . At the end, the results of observations before and after the introduction of enrichment techniques were compared and it was possible to observe significant changes in behavior such as run , walk and scratching . The animals were more active and spent longer visible during the day, the enrichment also increased the frequency of social behaviors and the end of the work occurred even attempted copulation , thus showing that the enrichment exerted a positive influence on the behavioral patterns of lesser grisson (Galictis cuja)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of the present study was to evaluate the behavioral patterns associated with autism and the prevalence of these behaviors in males and females, to verify whether our model of lipopolysaccharide (LPS) administration represents an experimental model of autism. For this, we prenatally exposed Wistar rats to LPS (100 mu g/kg, intraperitoneally, on gestational day 9.5), which mimics infection by gram-negative bacteria. Furthermore, because the exact mechanisms by which autism develops are still unknown, we investigated the neurological mechanisms that might underlie the behavioral alterations that were observed. Because we previously had demonstrated that prenatal LPS decreases striatal dopamine (DA) and metabolite levels, the striatal dopaminergic system (tyrosine hydroxylase [TH] and DA receptors D1a and D2) and glial cells (astrocytes and microglia) were analyzed by using immunohistochemistry, immunoblotting, and real-time PCR. Our results show that prenatal LPS exposure impaired communication (ultrasonic vocalizations) in male pups and learning and memory (T-maze spontaneous alternation) in male adults, as well as inducing repetitive/restricted behavior, but did not change social interactions in either infancy (play behavior) or adulthood in females. Moreover, although the expression of DA receptors was unchanged, the experimental animals exhibited reduced striatal TH levels, indicating that reduced DA synthesis impaired the striatal dopaminergic system. The expression of glial cell markers was not increased, which suggests that prenatal LPS did not induce permanent neuroinflammation in the striatum. Together with our previous finding of social impairments in males, the present findings demonstrate that prenatal LPS induced autism-like effects and also a hypoactivation of the dopaminergic system. (c) 2012 Wiley Periodicals, Inc.

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CONTEXT AND OBJECTIVES: Themes like alcohol and drug abuse, relationship difficulties, psychoses, autism and personality dissociation disorders have been widely used in films. Psychiatry and psychiatric conditions in various cultural settings are increasingly taught using films. Many articles on cinema and psychiatry have been published but none have presented any methodology on how to select material. Here, the authors look at the portrayal of abusive use of alcohol and drugs during the Brazilian cinema revival period (1994 to 2008). DESIGN AND SETTING: Qualitative study at two universities in the state of São Paulo. METHODS: Scenes were selected from films available at rental stores and were analyzed using a specifically designed protocol. We assessed how realistic these scenes were and their applicability for teaching. One author selected 70 scenes from 50 films (graded for realism and teaching applicability > 8). These were then rated by another two judges. Rating differences among the three judges were assessed using nonparametric tests (P < 0.001). Scenes with high scores (> 8) were defined as "quality scenes". RESULTS: Thirty-nine scenes from 27 films were identified as "quality scenes". Alcohol, cannabis, cocaine, hallucinogens and inhalants were included in these. Signs and symptoms of intoxication, abusive/harmful use and dependence were shown. CONCLUSIONS: We have produced rich teaching material for discussing psychopathology relating to alcohol and drug use that can be used both at undergraduate and at postgraduate level. Moreover, it could be seen that certain drug use behavioral patterns are deeply rooted in some Brazilian films and groups.

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The emergence and maintenance of maternal behavior are under the influence of environmental cues such as light and dark periods. This article discusses the characteristic neurobiology of the behavioral patterns of lactating rats. Specifically, the hormonal basis and neurocircuits that determine whether mother rats show typical sequential patterns of behavioral responses are discussed. During lactation, rats express a sequential pattern of behavioral parameters that may be determined by hormonal variations. Sensorial signals emitted by pups, as well as environmental cues, are suggested to serve as conditioned stimuli for these animals. Finally, the expression of maternal behavior is discussed under neuroeconomic and evolutionary perspectives.

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[ES] El presente artículo describe la problemática poblacional venezolana en relación con sus patrones de comportamiento (hábitos), que vienen causando un deterioro gradual de la salud. Refiere la reseña histórica de la Educación física partiendo de su incorporación en el currículo educativo, transitando por sus cambios y transformaciones hasta la actualidad. Aborda la educación física en Venezuela en correspondencia con las políticas educativas y de la actividad física para la salud. Presenta los programas que viene direccionando y desarrollando el Estado con la intencionalidad de crear conciencia hacia la importancia de la actividad física para contribuir, con disminución del sedentarismo, uno de los factores causantes de la obesidad a escala pandémica. Resalta las prácticas actuales asociadas con programas educacionales relacionados con la educación física y la salud. Por último describe programas innovadores, implementados en las instituciones educativas y en las comunidades para la adquisición de hábitos y patrones de conducta saludables.

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Die Entstehung eines Marktpreises für einen Vermögenswert kann als Superposition der einzelnen Aktionen der Marktteilnehmer aufgefasst werden, die damit kumulativ Angebot und Nachfrage erzeugen. Dies ist in der statistischen Physik mit der Entstehung makroskopischer Eigenschaften vergleichbar, die von mikroskopischen Wechselwirkungen zwischen den beteiligten Systemkomponenten hervorgerufen werden. Die Verteilung der Preisänderungen an Finanzmärkten unterscheidet sich deutlich von einer Gaußverteilung. Dies führt zu empirischen Besonderheiten des Preisprozesses, zu denen neben dem Skalierungsverhalten nicht-triviale Korrelationsfunktionen und zeitlich gehäufte Volatilität zählen. In der vorliegenden Arbeit liegt der Fokus auf der Analyse von Finanzmarktzeitreihen und den darin enthaltenen Korrelationen. Es wird ein neues Verfahren zur Quantifizierung von Muster-basierten komplexen Korrelationen einer Zeitreihe entwickelt. Mit dieser Methodik werden signifikante Anzeichen dafür gefunden, dass sich typische Verhaltensmuster von Finanzmarktteilnehmern auf kurzen Zeitskalen manifestieren, dass also die Reaktion auf einen gegebenen Preisverlauf nicht rein zufällig ist, sondern vielmehr ähnliche Preisverläufe auch ähnliche Reaktionen hervorrufen. Ausgehend von der Untersuchung der komplexen Korrelationen in Finanzmarktzeitreihen wird die Frage behandelt, welche Eigenschaften sich beim Wechsel von einem positiven Trend zu einem negativen Trend verändern. Eine empirische Quantifizierung mittels Reskalierung liefert das Resultat, dass unabhängig von der betrachteten Zeitskala neue Preisextrema mit einem Anstieg des Transaktionsvolumens und einer Reduktion der Zeitintervalle zwischen Transaktionen einhergehen. Diese Abhängigkeiten weisen Charakteristika auf, die man auch in anderen komplexen Systemen in der Natur und speziell in physikalischen Systemen vorfindet. Über 9 Größenordnungen in der Zeit sind diese Eigenschaften auch unabhängig vom analysierten Markt - Trends, die nur für Sekunden bestehen, zeigen die gleiche Charakteristik wie Trends auf Zeitskalen von Monaten. Dies eröffnet die Möglichkeit, mehr über Finanzmarktblasen und deren Zusammenbrüche zu lernen, da Trends auf kleinen Zeitskalen viel häufiger auftreten. Zusätzlich wird eine Monte Carlo-basierte Simulation des Finanzmarktes analysiert und erweitert, um die empirischen Eigenschaften zu reproduzieren und Einblicke in deren Ursachen zu erhalten, die zum einen in der Finanzmarktmikrostruktur und andererseits in der Risikoaversion der Handelsteilnehmer zu suchen sind. Für die rechenzeitintensiven Verfahren kann mittels Parallelisierung auf einer Graphikkartenarchitektur eine deutliche Rechenzeitreduktion erreicht werden. Um das weite Spektrum an Einsatzbereichen von Graphikkarten zu aufzuzeigen, wird auch ein Standardmodell der statistischen Physik - das Ising-Modell - auf die Graphikkarte mit signifikanten Laufzeitvorteilen portiert. Teilresultate der Arbeit sind publiziert in [PGPS07, PPS08, Pre11, PVPS09b, PVPS09a, PS09, PS10a, SBF+10, BVP10, Pre10, PS10b, PSS10, SBF+11, PB10].

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Ethical scandals in business have led to calls for more ethical or moral leadership. Yet, we still know very little about what characterizes ethical leadership and what its positive consequences actually are. We argue that the major question is not about what leaders value, but rather whether their ethical values are regularly reflected in behavioral patterns across situations and situational challenges. To address this, we have begun to build the Ethical Leadership Behavior Scale, which is based on behaviors reflecting concrete manifestations of ethical values (e.g., fairness, respect) across occasions and situational barriers. A study with 592 employees of 110 work units in two departments provided a first test of this scale and demonstrated that the level of ethical leadership behavior predicts important work-related attitudes (job satisfaction, work engagement, affective organizational commitment) and outcomes (health complaints, emotional exhaustion, absenteeism).

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The social processes that lead to destructive behavior in celebratory crowds can be studied through an agent-based computer simulation. Riots are an increasingly common outcome of sports celebrations, and pose the potential for harm to participants, bystanders, property, and the reputation of the groups with whom participants are associated. Rioting cannot necessarily be attributed to the negative emotions of individuals, such as anger, rage, frustration and despair. For instance, the celebratory behavior (e.g., chanting, cheering, singing) during UConn’s “Spring Weekend” and after the 2004 NCAA Championships resulted in several small fires and overturned cars. Further, not every individual in the area of a riot engages in violence, and those who do, do not do so continuously. Instead, small groups carry out the majority of violent acts in relatively short-lived episodes. Agent-based computer simulations are an ideal method for modeling complex group-level social phenomena, such as celebratory gatherings and riots, which emerge from the interaction of relatively “simple” individuals. By making simple assumptions about individuals’ decision-making and behaviors and allowing actors to affect one another, behavioral patterns emerge that cannot be predicted by the characteristics of individuals. The computer simulation developed here models celebratory riot behavior by repeatedly evaluating a single algorithm for each individual, the inputs of which are affected by the characteristics of nearby actors. Specifically, the simulation assumes that (a) actors possess 1 of 5 distinct social identities (group memberships), (b) actors will congregate with actors who possess the same identity, (c) the degree of social cohesion generated in the social context determines the stability of relationships within groups, and (d) actors’ level of aggression is affected by the aggression of other group members. Not only does this simulation provide a systematic investigation of the effects of the initial distribution of aggression, social identification, and cohesiveness on riot outcomes, but also an analytic tool others may use to investigate, visualize and predict how various individual characteristics affect emergent crowd behavior.

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This study examines the reduction in hospital utilization of 393 public hospital patients who were referred to the hospital's alcoholism screening program for intervention. The 393 patients were the total patient population of the alcoholism screening program for the period of September through December, 1982. Medical records of these patients were investigated to assess the total number of hospital days six months before and six months after intervention. The findings support the hypothesis of decreased utilization. The total number of hospital days for 393 patients before intervention of the alcoholism program was 3,458, with a mean length of stay of 8.80 days. The total number of hospital days after intervention was 458 days, with a mean length of stay of 6.50 days. The average individual difference (decrease) was 7.63 days for one year. From a total of 393 patients counseled by the alcoholism program, 106 (27%) went to treatment for their alcoholism. Other aims were to examine the referral sources (physicians, nurses, social workers and the MAST); study the impact of familial history of alcoholism on referrals, and explore the MAST scores of patients successfully referred. Implications of the study are that it would benefit the public hospital, with their disproportionate numbers of alcoholics, to intervene in the behavioral patterns of alcoholism. Such intervention would be a factor in reducing the overall hospitalization of the alcoholic. ^

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Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

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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.