Big Data and the Fabric of Human Geography

Digital data tracking what we do, the time and place of our actions, and the chains of interdependence that link those actions together, help us draw a richer picture of human geography as it unfolds in its multiple layers. This commentary briefly illustrates the type of maps and models we can build with that data as well as some important challenges that arise from their complexity and unsolved validity concerns

Capitalizing on Social Media Analysis – Insights from an Online Review on Business Models

With the rise and proliferation of social media on the Internet, social media analysis is emerging as a new business model for software companies. The purpose of this paper is to provide a systematic overview of different types of such business models. After developing a coding schema based on the business model, we conducted an in-depth analysis of 16 websites of companies that actively promote social media analysis to their clients. We identified three archetypes of business models in this area: specialist content analysts, social data and application integrator, and social media service provider. Future research can build on these insights in order to focus on designing or revising methods for social media analysis to realize either of these business models. Software companies can benefit from the results by positioning their own business models in this emerging market more thoughtfully

Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags

In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’

Detection of Sarcasm and Nastiness: New Resources for Spanish Language

The main goal of this work is to provide the cognitive computing community with valuable resources to analyze and simulate the intentionality and/or emotions embedded in the language employed in social media. Specifically, it is focused on the Spanish language and online dialogues, leading to the creation of SOFOCO (Spanish Online Forums Corpus). It is the first Spanish corpus consisting of dialogic debates extracted from social media and it is annotated by means of crowdsourcing in order to carry out automatic analysis of subjective language forms, like sarcasm or nastiness. Furthermore, the annotators were also asked about the context need when taking a decision. In this way, the users’ intentions and their behavior inside social networks can be better understood and more accurate text analysis is possible. An analysis of the annotation results is carried out and the reliability of the annotations is also explored. Additionally, sarcasm and nastiness detection results (around 0.76 F-Measure in both cases) are also reported. The obtained results show the presented corpus as a valuable resource that might be used in very diverse future work.This study was partially funded by the Spanish Government (TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R) by the European Unions’s H2020 program under grant 769872 and by the National Science Foundation of USA (NSF CISE R1 #1202668

A large-scale sentiment analysis for Yahoo! answers

Sentiment extraction from online web documents has re-cently been an active research topic due to its potential use in commercial applications. By sentiment analysis, we refer to the problem of assigning a quantitative positive/negative mood to a short bit of text. Most studies in this area are limited to the identification of sentiments and do not inves-tigate the interplay between sentiments and other factors. In this work, we use a sentiment extraction tool to investi-gate the influence of factors such as gender, age, education level, the topic at hand, or even the time of the day on sen-timents in the context of a large online question answering site. We start our analysis by looking at direct correlations, e.g., we observe more positive sentiments on weekends, very neutral ones in the Science & Mathematics topic, a trend for younger people to express stronger sentiments, or people in military bases to ask the most neutral questions. We then extend this basic analysis by investigating how properties of the (asker, answerer) pair affect the sentiment present in the answer. Among other things, we observe a dependence on the pairing of some inferred attributes estimated by a user’s ZIP code. We also show that the best answers differ in their sentiments from other answers, e.g., in the Business & Finance topic, best answers tend to have a more neutral sentiment than other answers. Finally, we report results for the task of predicting the attitude that a question will provoke in answers. We believe that understanding factors influencing the mood of users is not only interesting from a sociological point of view, but also has applications in ad-vertising, recommendation, and search

Digital design for an ageing society

An ageing population and the progression of technology is the context for this practice-led research project. Through studying the relationship between older people and technology the research’s primary aim is to explore computer interactions aimed at older people. An inquisitive visual design practice was proposed to help stimulate debate and examine the effectiveness of design for health and wellbeing in a digital context. Many difficulties surrounding older people and their relationship with technology were identified during this research. As well as the obvious physical disabilities such as reduced mobility, dexterity issues and reduced eyesight, other issues less apparent include reduced memory, stereotyping and isolation. A reluctance to adopt new technologies, and in some cases avoid them altogether was identified in this demographic grouping as a significant problem too. The practice element of the thesis incorporates the design of an iPad app prototype, which uses food as a vehicle to facilitate the research by investigating for example: typography, colour and layout. The design process is informed by findings from a literature review coupled with a heuristic approach to interaction design. Two qualitative focus groups were conducted with a variety of computer users and non-users. Participants discussed their relationships with computers and how they are perceived. They also gave responses after testing the app prototype and completed a questionnaire based on focus group activities. The results from both sessions concluded that the majority of older people are interested in computers and what they have to offer, but often find it difficult to know where to begin. The importance of patience and consistency when introducing an app to older people was also observed. Some participants were frustrated by inconsistent user interfaces. As a result a set of accessible guidelines is suggested to engage with designers, policy makers and service providers