The nature of twitter trending topics: Analysing intrinsic factors associated with the twitter ecosystem

© 2018 The authors and IOS Press. All rights reserved. We are inundated with data—companies such as Twitter deal with petabytes of information on a daily basis. However, some users, especially the new ones, often find it difficult to cope with the overwhelming and disorganised deluge of information. Scientists have already worked out ways to identify Twitter trending topics, as a means to index information and make sense of it. However, we know little about the impact on trending topics of various intrinsic factors associated with the Twitter ecosystem. For example, anecdotal evidence suggests that trending topics are characterised by highly polarised tweets, or that large audiences typically host the emergence of trending topics. However, no study has yet addressed these issues formally. To remedy this situation, we have launched an investigation on the nature of trending topics. Our initial observations indicate that there is a correlation between strong sentiment polarity and the emergence of trending topics—we can also confirm that the strength of the polarity drops as the trending topics fade away. Conversely, our experiments highlight that there is no correlation between the size of a Twitter audience and the rise of trending topics

Social Media

In this chapter you will: 1) understand the dynamics of social media-based communities, their composition and behaviours 2) learn to conduct a social media audit including competitor analysis 3) recognise the importance of a blog as a centre of digital presence development 4) use amplification strategies to develop brand presence explore the concept of social capital and its relationship to brand engagement activities 5) develop tactics for measuring social media based, their quality and quantity

Measurements and analysis of individual and collective advertising

The fundamental problem of the online advertising ecosystem is its lack of transparency, which avoid people or advertisers to properly understand its functionality. This lack of transparency may jeopardize the sustainable growth of this profitable market. The research community has understood this message and has recently started to develop methodologies and tools to unveil relevant aspects of online advertising. The results of this thesis aim to contribute to this collective effort. We define two different types of advertising, individual advertising and collective advertising, both present in the context of online advertising. (i) In the context of this thesis, we define individual advertising as the advertising that is targeted directly to a single user. People, as Internet users, browse over the millions and millions of websites that make up the Internet. Each of their single steps, leaves a unique footprint that defines us as a single online individual (e.g. country, sex, age, interests, tastes, etc.) who can be potentially targeted by the advertising ecosystem. (ii) Collective advertising refers to a group of users with common characteristics. For example, same geographical area (i.e. region, city, country, etc.) or same age range. Due to the nature of this type of advertising, the study has been conducted in an Online Social Network (OSN), Twitter, and specifically we have analyzed the functionality known as Trending Topics due to being a powerful tool used in marketing and advertising contexts. This thesis presents two independent methodologies in these types of advertising, which help to unveil fundamental aspects of the practices in the advertising ecosystem. One of the key problems of individual advertising is privacy. As Internet users, the sites we visite, the clicks we do or the emails we send, define us perfectly facing the advertising ecosystem. This wealth of information allows customized campaigns for each user but also includes a huge risk to our privacy and the use of our personal data. Then, the first contribution of this thesis is to define a methodology to analyze the current use of Online Behavioural targeted Advertising (OBA) that has risen in prominence as a method to increase the effectiveness of online advertising but also has a negative impact on user privacy. OBA operates by associating tags or labels to users based on their online activity and then using these labels to target them. This rise has been accompanied by privacy concerns from researchers, regulators and the press. This thesis presents a novel methodology for measuring and understanding OBA in the online advertising market. We rely on training artificial online personas representing behavioural traits like “cooking”, “movies”, “motor sports”, etc. and build a measurement system that is automated, scalable and supports testing of multiple configurations. We observe that OBA is a frequent practice and notice that categories valued more by advertisers are more intensely targeted. In the context of collective advertising, there exists a lack of methodologies to quantify the efficiency of online collective advertising tools and comparing it with the efficiency of traditional collective advertising channels (e.g., ads in TV, radio, newspapers). In this thesis we address this problem and propose the first methodology to characterize the visibility of Trending Topics in several countries and cities by using metrics that rely on the exposure time of Trending Topics and the penetration of Twitter, we compare the visibility provided by Trending Topics and traditional advertisement channels such as newspapers’ ads or radio-stations’ commercials for several countries. The study confirms that Trending Topics offer a comparable visibility to the aforementioned traditional advertisement channels in those countries where we have conducted our comparison study. Also, collective advertising, given its nature, allows the information to be spread among different users of the social network via comments or shares. This feature converts the collective advertising in a piece of information with a different treatment comparing to the individual advertising and, therefore, it also requires a study of this spread of information. To this end, we have conducted a study on existing patterns across countries following a leader-follower model over a dataset of thousands of Trending Topics from dozens of countries and hundreds of cities. The conclusions drawn from this thesis have allowed a better understanding of the use of online advertising on the web, providing more transparency to the advertising ecosystem and quantifying the impact of new collective advertising tools.El problema fundamental del ecosistema de publicidad online es su falta de transparencia, evitando que los usuarios y los anunciantes comprendan adecuadamente su funcionamiento. Esta falta de transparencia puede poner en peligro el crecimiento sostenible de este mercado tan rentable. La comunidad investigadora ha comprendido este problema y recientemente ha comenzado a desarrollar metodologías y herramientas para dar a conocer los aspectos más relevantes de la publicidad online. Los resultados de esta tesis tienen como objetivo contribuir a este esfuerzo colectivo. En esta tesis se definen dos tipos diferentes de publicidad dentro del contexto de la publicidad online: la publicidad individual y la publicidad colectiva. (i) En el contexto de esta tesis, hemos definido la publicidad individual como la publicidad que se dirige directamente a un usuario con unas características concretas. Las personas navegan a través de millones y millones de sitios web que conforman Internet. Cada uno de nuestros pasos en Internet, deja una huella única que nos define como un individuo único (por ejemplo, nuestro país, sexo, edad, intereses, gustos, etc.) y que puede ser potencialmente utilizada por el ecosistema de publicidad. (ii) Por otro lado, la publicidad colectiva se refiere a un grupo de usuarios con características comunes. Por ejemplo, una misma zona geográfica (región, ciudad, país, etc.) o en el mismo rango de edad. Debido a la naturaleza de este tipo de publicidad, el estudio se ha llevado a cabo en una red social concreta, Twitter, y específicamente, hemos analizado la funcionalidad conocida como Trending Topics, al ser una herramienta válida para ser utilizada en los contextos de marketing y publicidad. En esta tesis se presentan dos metodologías independientes relacionadas con los tipos de publicidad definidas anteriormente. Estas metodologías permitirán dar a conocer aspectos fundamentales de las prácticas utilizadas en el ecosistema de publicidad. Uno de los problemas clave de la publicidad individual es la privacidad. Como internautas, los sitios que visitamos, los clics que hacemos o los correos electrónicos que enviamos, nos definen a la perfección de cara al ecosistema de publicidad. Por tanto, esta gran cantidad de información hace posible, no solo campañas personalizadas para cada usuario, sino que también incluye un gran riesgo para nuestra privacidad y el uso de nuestros datos personales. Por tanto, la primera contribución de esta tesis es definir una metodología para analizar el uso actual del Online Behavioural Advertising (OBA) que ha incrementado su importancia como método para aumentar la eficacia de la publicidad online, pero que también tiene un impacto negativo sobre la privacidad del usuario. OBA funciona mediante la asociación de tags o etiquetas a los usuarios en función de su actividad online para luego usar estas etiquetas para realizar campañas dirigidas a ellos. El aumento de esta técnica se ha visto acompañado por una mayor preocupación sobre la privacidad de los usuarios por parte de los investigadores, los reguladores y la prensa. Esta tesis presenta una nueva metodología para medir y comprender OBA en el mercado de la publicidad online. Esta metodología se basa en la creación de personas artificiales con intereses y gustos distintos como “la cocina”, “cine”, “deportes de motor”, etc. A su vez, hemos desarrollado un sistema de medición automático, escalable que permite realizar pruebas con múltiples configuraciones. Como resultado cabe mencionar que hemos observado que OBA es una práctica frecuente y que los intereses mejor valorados por los anunciantes son utilizados con mayor intensidad en las campañas dirigidas. Por otro lado, en el contexto de la publicidad colectiva, faltan metodologías que permitan cuantificar la eficacia de las actuales herramientas publicitarias colectivas y también realizar estudios comparativos con la eficiencia de los canales de publicidad colectiva tradicionales (anuncios en televisión, radio, periódicos...). En esta tesis se aborda este problema y se propone una metodología para caracterizar la visibilidad de los Trending Topics en varios países y ciudades mediante el uso de métricas basadas en el tiempo de exposición de los Trending Topics y la penetración de Twitter en esas zonas geográficas. Además, comparamos en varios países la visibilidad que proporcionan los Trending Topics y los canales de publicidad tradicionales (por ejemplo, los anuncios en periódicos o en la radio). Este estudio confirma que los Trending Topics ofrecen una visibilidad comparable a los canales de publicidad tradicionales en los países en los que hemos realizado el estudio comparativo. Además, la publicidad colectiva, debido a su naturaleza, permite que la información se difunda fácilmente entre los diferentes usuarios de una red social a través de los comentarios. Esta característica convierte la publicidad colectiva en una pieza de información con un tratamiento diferente a la publicidad individual y, por lo tanto, se requiere un estudio adicional de la propagación de esta información. Con este fin, se ha realizado un estudio sobre los patrones existentes entre países siguiendo un modelo líder-seguidor sobre un conjunto de datos de miles de Trending Topics en decenas de países y cientos de ciudades. Las conclusiones extraídas de esta tesis han permitido una mejor comprensión de la utilización de la publicidad online en la web, proporcionando una mayor transparencia al ecosistema de publicidad y cuantificando el impacto de las nuevas herramientas publicitarias colectivas.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Secretario: Juan Caballero Bayerri.- Vocal: Pere Baret Ro

Exploring Sentiment Analysis on Twitter: Investigating Public Opinion on Migration in Brazil from 2015 to 2020

openTechnology has reshaped societal interaction and the expression of opinions. Migration is a prominent trend, and analysing social media discussions provides insights into societal perspectives. This thesis explores how events between 2015 and 2020 impacted Brazilian sentiment on Twitter about migrants and refugees. Its aim was to uncover the influence of key sociopolitical events on public sentiment, clarifying how these echoed in the digital realm. Four key objectives guided this research: (a) understanding public opinions on migrants and refugees, (b) investigating how events influenced Twitter sentiment, (c) identifying terms used in migration-related tweets, and (d) tracking sentiment shifts, especially concerning changes in government. Sentiment analysis using VADER (Valence Aware Dictionary and sEntiment Reasoner) was employed to analyse tweet data. The use of computational methods in social sciences is gaining traction, yet no analysis has been conducted before to understand the sentiments of the Brazilian population regarding migration. The analysis underscored Twitter's role in reflecting and shaping public discourse, offering insights into how major events influenced discussions on migration. In conclusion, this study illuminated the landscape of Brazilian sentiment on migration, emphasizing the significance of innovative social media analysis methodologies for policymaking and societal inclusivity in the digital age

Using Social Media as a Source for Understanding Public Perceptions of Archaeology: Research Challenges and Methodological Pitfalls

Digital social science research has had an important impact on the types of methodological approaches to the internet and digital social phenomena, practices and communities. Whilst this paper does not seek to include empirical data, it aims to elaborate further on these debates in digital social research, that is, research on ‘life in digital society’ (Lindgren 2017: 230), using insights from my own research methods. This paper will firstly consider some methodological pitfalls that could sabotage our digital social archaeology research. It will then discuss the importance of understanding the framework and sources of our data. It will outline the two main methodological approaches I have used in my own empirical research to date – ‘thick’ social media data collection and analysis, and digital ethnography. It will discuss some of the many ethical considerations that must be assessed and implemented when undertaking this type of work. I will argue for a methodological pragmatism when undertaking social research in the fields of archaeology and heritage, although this pragmatism can be applied to any field of social study in the digital world