Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Imaging, Keyboarding, and Posting Identities: Young People and New Media Technologies

Part of the Volume on Youth, Identity, and Digital Media Clicking, posting, and text messaging their way through a shifting digital landscape, young people are bending and blending genres, incorporating old ideas, activities, and images into new bricolages, changing the face, if not the substance, of social interaction and altering how they see themselves and each other. From data collected in Britain, Canada, and South Africa, we have selected cases that involve a range of technologies and contexts, from adult-mediated activities in schools and community centers to spontaneous media production done in private at home. Whether it be postings on websites, improvisations in video production, or the incorporation of objects in a multi-media presentation, these cases illustrate that, like digital cultural production, identity processes are multifaceted and in flux, constructed and deconstructed through a process of bricolage that we label as "identities-in-action." Analysis of the cases reveals certain shared features of digital production that contribute to identities-in-action: the "constructedness" of production, the collective and social aspects of individual productions, the neglected but crucial element of embodiment, the reflexivity and negotiation involved in producing and consuming one's own images, the creativity in media convergence, and the value of constructivist models of learning

Understanding “influence”: An exploratory study of academics’ process of knowledge construction through iterative and interactive information seeking

The motivation for this study is to better understand the searching and sensemaking processes undertaken to solve exploratory tasks for which people lack pre-existing frames. To investigate people’s strategies for that type of task, we focused on “influence” tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. This qualitative study reports the process undertaken by academics of different levels of seniority to complete exploratory search tasks that involved identifying influential members of their academic community and “rising stars, ” and to identify similar roles in an unfamiliar academic community. 11 think-aloud sessions followed by semi-structured interviews were conducted to investigate the role of specific and general domain expertise in the process of information seeking and knowledge construction. Academics defined and completed the task through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of “being influential”. Elements of the Data/Frame Theory of Sensemaking (Klein et al., 2007) were used as sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill-defined or non-existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence

HiER 2015. Proceedings des 9. Hildesheimer Evaluierungs- und Retrievalworkshop

Die Digitalisierung formt unsere Informationsumwelten. Disruptive Technologien dringen verstärkt und immer schneller in unseren Alltag ein und verändern unser Informations- und Kommunikationsverhalten. Informationsmärkte wandeln sich. Der 9. Hildesheimer Evaluierungs- und Retrievalworkshop HIER 2015 thematisiert die Gestaltung und Evaluierung von Informationssystemen vor dem Hintergrund der sich beschleunigenden Digitalisierung. Im Fokus stehen die folgenden Themen: Digital Humanities, Internetsuche und Online Marketing, Information Seeking und nutzerzentrierte Entwicklung, E-Learning

Open Research

Open Research is an open textbook based on the award winning course of the same name. The course ran two facilitated iterations during 2014 and 2015 on Peer 2 Peer University (P2PU). Open Research was co-authored and delivered by the OER Hub team, leaders in open education research and open research practices. Open Research explores what it means to be more 'open' in your research, ethical considerations, dissemination and the role of reflection. This open textbook also incorporates previous participant contributions into new activity commentary sections

Encouraging serendipity in research: designing technologies to support connection-making

Mobile applications have the ability to present information to users that is influenced by their surroundings, activities and interests. Such applications have the potential to influence the likelihood of individuals experiencing ‘serendipity’, through a combination of information, context, insight and activity. This study reports the deployment of a system that sends push text suggestions to users throughout the day, where the content of those messages is informed by users’ experience and interests. We investigated the responses to and interactions with messages that varied in format and relevance, and which were received at different times throughout the day. Sixteen participants were asked to use a mobile diary application to record their experiences and thoughts regarding information that was received over a period of five consecutive days. Results suggest that participants’ perception of the received suggestions was influenced by the relevance of the suggestion to their interests, but that there were also positive attitudes towards seemingly irrelevant information. Qualitative data indicates that participants, if in an appropriate time and place, are willing to accept and act upon push suggestions as long as the number of suggestions that they receive is not overwhelming. This study contributes towards an understanding of how mobile users make connections with new information, furthering our understanding of how serendipitous connections and insightful thinking could be accommodated using technology

プレイス・ブランディングの開発を目的としたソーシャルネットワークデータを介した公園訪問者の認識調査に関する研究

Place branding refers to the development of brands for geographical locations. City of Bandung Indonesia has its own approach to build city\u27s image. This city creates its image trough the development of public city parks to the thematic park concept. The provision of thematic park become a key attraction at the city service scale and provide entertainment and recreation for urban communities through their new physical design and attractive facilities. Therefore, assessments on the perceptions of parks\u27 visitors are needed to determine if the parks are well-known to the wider community. The assessment can also be utilized to measure to what extent the influence of thematic parks for place branding. Social networks data by online reviews is used to identify whether a certain branding is successful or not by looking at the user\u27s opinion. The aims of this study are to investigate parks visitors\u27 perceptions using social networks data to develop place branding and to evaluate if the existing parks correlates to other determinant factors in the place branding. Study found that, social network data shows great promise in assessing visitors\u27 perceptions. Assessments provide an overview of the attractiveness of thematic parks and how they are known to wider community as a type of place branding for the city of Bandung.北九州市立大

Affect-based information retrieval

One of the main challenges Information Retrieval (IR) systems face nowadays originates from the semantic gap problem: the semantic difference between a user’s query representation and the internal representation of an information item in a collection. The gap is further widened when the user is driven by an ill-defined information need, often the result of an anomaly in his/her current state of knowledge. The formulated search queries, which are submitted to the retrieval systems to locate relevant items, produce poor results that do not address the users’ information needs. To deal with information need uncertainty IR systems have employed in the past a range of feedback techniques, which vary from explicit to implicit. The first category of feedback techniques necessitates the communication of explicit relevance judgments, in return for better query reformulations and recommendations of relevant results. However, the latter happens at the expense of users’ cognitive resources and, furthermore, introduces an additional layer of complexity to the search process. On the other hand, implicit feedback techniques make inferences on what is relevant based on observations of user search behaviour. By doing so, they disengage users from the cognitive burden of document rating and relevance assessments. However, both categories of RF techniques determine topical relevance with respect to the cognitive and situational levels of interaction, failing to acknowledge the importance of emotions in cognition and decision making. In this thesis I investigate the role of emotions in the information seeking process and develop affective feedback techniques for interactive IR. This novel feedback framework aims to aid the search process and facilitate a more natural and meaningful interaction. I develop affective models that determine topical relevance based on information gathered from various sensory channels, and enhance their performance using personalisation techniques. Furthermore, I present an operational video retrieval system that employs affective feedback to enrich user profiles and offers meaningful recommendations of unseen videos. The use of affective feedback as a surrogate for the information need is formalised as the Affective Model of Browsing. This is a cognitive model that motivates the use of evidence extracted from the psycho-somatic mobilisation that occurs during cognitive appraisal. Finally, I address some of the ethical and privacy issues that arise from the social-emotional interaction between users and computer systems. This study involves questionnaire data gathered over three user studies, from 74 participants of different educational background, ethnicity and search experience. The results show that affective feedback is a promising area of research and it can improve many aspects of the information seeking process, such as indexing, ranking and recommendation. Eventually, it may be that relevance inferences obtained from affective models will provide a more robust and personalised form of feedback, which will allow us to deal more effectively with issues such as the semantic gap

Mind Economy: Dynamic Graph Analysis of Communications

Social networks are growing in reach and impact but little is known about their structure, dynamics, or users’ behaviors. New techniques and approaches are needed to study and understand why these networks attract users’ persistent attention, and how the networks evolve. This thesis investigates questions that arise when modeling human behavior in social networks, and its main contributions are: • an infrastructure and methodology for understanding communication on graphs; • identification and exploration of sub-communities; • metrics for identifying effective communicators in dynamic graphs; • a new definition of dynamic, reciprocal social capital and its iterative computation • a methodology to study influence in social networks in detail, using • a class hierarchy established by social capital • simulations mixed with reality across time and capital classes • various attachment strategies, e.g. via friends-of-friends or full utility optimization • a framework for answering questions such as “are these influentials accidental” • discovery of the “middle class” of social networks, which as shown with our new metrics and simulations is the real influential in many processes Our methods have already lead to the discovery of “mind economies” within Twitter, where interactions are designed to increase ratings as well as promoting topics of interest and whole subgroups. Reciprocal social capital metrics identify the “middle class” of Twitter which does most of the “long-term” talking, carrying the bulk of the system-sustaining conversations. We show that this middle class wields the most of the actual influence we should care about — these are not “accidental influentials.” Our approach is of interest to computer scientists, social scientists, economists, marketers, recruiters, and social media builders who want to find and present new ways of exploring, browsing, analyzing, and sustaining online social networks