Showing papers on "Social media published in 2015"
TL;DR: Examination of the news that millions of Facebook users' peers shared, what information these users were presented with, and what they ultimately consumed found that friends shared substantially less cross-cutting news from sources aligned with an opposing ideology.
Abstract: Exposure to news, opinion and civic information increasingly occurs through social media. How do these online networks influence exposure to perspectives that cut across ideological lines? Using de-identified data, we examined how 10.1 million U.S. Facebook users interact with socially shared news. We directly measured ideological homophily in friend networks, and examine the extent to which heterogeneous friends could potentially expose individuals to cross-cutting content. We then quantified the extent to which individuals encounter comparatively more or less diverse content while interacting via Facebook’s algorithmically ranked News Feed, and further studied users’ choices to click through to ideologically discordant content. Compared to algorithmic ranking, individuals’ choices about what to consume had a stronger effect limiting exposure to cross-cutting content.
2,014 citations
TL;DR: A rigorous survey on sentiment analysis is presented, which portrays views presented by over one hundred articles published in the last decade regarding necessary tasks, approaches, and applications of sentiment analysis.
Abstract: With the advent of Web 2.0, people became more eager to express and share their opinions on web regarding day-to-day activities and global issues as well. Evolution of social media has also contributed immensely to these activities, thereby providing us a transparent platform to share views across the world. These electronic Word of Mouth (eWOM) statements expressed on the web are much prevalent in business and service industry to enable customer to share his/her point of view. In the last one and half decades, research communities, academia, public and service industries are working rigorously on sentiment analysis, also known as, opinion mining, to extract and analyze public mood and views. In this regard, this paper presents a rigorous survey on sentiment analysis, which portrays views presented by over one hundred articles published in the last decade regarding necessary tasks, approaches, and applications of sentiment analysis. Several sub-tasks need to be performed for sentiment analysis which in turn can be accomplished using various approaches and techniques. This survey covering published literature during 2002-2015, is organized on the basis of sub-tasks to be performed, machine learning and natural language processing techniques used and applications of sentiment analysis. The paper also presents open issues and along with a summary table of a hundred and sixty-one articles.
1,011 citations
TL;DR: In this article, the authors employed a content analysis of the creative strategies present in the social media content shared by a sample of top brands to reveal which social media channels were being used, which creative strategies/appeals are being used and how these channels and strategies relate to consumer engagement in branded social media.
Abstract: This study employed a content analysis of the creative strategies present in the social media content shared by a sample of top brands. The results reveal which social media channels are being used, which creative strategies/appeals are being used, and how these channels and strategies relate to consumer engagement in branded social media. Past research has suggested that brands should focus on maintaining a social presence across social channels with content that is fresh and frequent and includes incentives for consumer participation (Ling et al., 2004). This study confirmed the importance of frequent updates and incentives for participation. In addition, several creative strategies were associated with customer engagement, specifically experiential, image, and exclusivity messages. Despite the value of these creative approaches, most branded social content can be categorized as functional.
933 citations
TL;DR: In this paper, the authors aim to delineate the meaning, conceptual boundaries and dimensions of consumer engagement within the context of online brand communities both in terms of the engagement with the brand and the other members of the online brand community.
Abstract: Purpose – This paper aims to delineate the meaning, conceptual boundaries and dimensions of consumer engagement within the context of online brand communities both in term of the engagement with the brand and the other members of the online brand communities. It also explores the relationships of consumer engagement with other concepts, suggesting antecedents of engagement. Design/methodology/approach – Data are collected through semi-structured interviews with 21 international online brand community members, covering a variety of brand categories and social media platforms. Findings – This paper suggests that individuals are engaging in online communities in social network platforms both with other individuals and with brands. The study also identifies three key engagement dimensions (cognition, affect and behaviours). Their meaning and sub-dimensions are investigated. The paper further suggests key drivers, one outcome and objects of consumer engagement in online brand communities. These findings are in...
809 citations
TL;DR: In this article, the authors discuss how and why social media platforms have become powerful sites for documenting and challenging episodes of police brutality and the misrepresentation of racialized bodies in mainstream media.
Abstract: As thousands of demonstrators took to the streets of Ferguson, Missouri, to protest the fatal police shooting of unarmed African American teenager Michael Brown in the summer of 2014, news and commentary on the shooting, the protests, and the militarized response that followed circulated widely through social media networks. Through a theorization of hashtag usage, we discuss how and why social media platforms have become powerful sites for documenting and challenging episodes of police brutality and the misrepresentation of racialized bodies in mainstream media. We show how engaging in “hashtag activism” can forge a shared political temporality, and, additionally, we examine how social media platforms can provide strategic outlets for contesting and reimagining the materiality of racialized bodies. Our analysis combines approaches from linguistic anthropology and social movements research to investigate the semiotics of digital protest and to interrogate both the possibilities and the pitfalls of engaging in “hashtag ethnography.”
754 citations
TL;DR: In this article, the authors present the results of a meta-analysis of research on social media use and participation, concluding that more than 80% of the metadata demonstrate a positive relationship between social media usage and participation.
Abstract: Social media has skyrocketed to popularity in the past few years. The Arab Spring in 2011 as well as the 2008 and 2012 Obama campaigns have fueled interest in how social media might affect citizens’ participation in civic and political life. In response, researchers have produced 36 studies assessing the relationship between social media use and participation in civic and political life. This manuscript presents the results of a meta-analysis of research on social media use and participation. Overall, the metadata demonstrate a positive relationship between social media use and participation. More than 80% of coefficients are positive. However, questions remain about whether the relationship is causal and transformative. Only half of the coefficients were statistically significant. Studies using panel data are less likely to report positive and statistically significant coefficients between social media use and participation, compared to cross-sectional surveys. The metadata also suggest that social media...
722 citations
TL;DR: This survey surveys the state of the art regarding computational methods to process social media messages and highlights both their contributions and shortcomings, and methodically examines a series of key subproblems ranging from the detection of events to the creation of actionable and useful summaries.
Abstract: Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information to gain insight into the situation as it unfolds. In particular, many social media messages communicated during emergencies convey timely, actionable information. Processing social media messages to obtain such information, however, involves solving multiple challenges including: parsing brief and informal messages, handling information overload, and prioritizing different types of information found in messages. These challenges can be mapped to classical information processing operations such as filtering, classifying, ranking, aggregating, extracting, and summarizing. We survey the state of the art regarding computational methods to process social media messages and highlight both their contributions and shortcomings. In addition, we examine their particularities, and methodically examine a series of key subproblems ranging from the detection of events to the creation of actionable and useful summaries. Research thus far has, to a large extent, produced methods to extract situational awareness information from social media. In this survey, we cover these various approaches, and highlight their benefits and shortcomings. We conclude with research challenges that go beyond situational awareness, and begin to look at supporting decision making and coordinating emergency-response actions.
710 citations
TL;DR: A causal-chain framework was developed based on the input-moderator-mediator-output model to illustrate the causality between the research constructs used and the conceptualization of theoretical models/theories proposed by previous researchers.
627 citations
TL;DR: A comprehensive review of online, official, and scientific literature was carried out in 2012-13 to develop a framework of disaster social media, illustrating that a variety of entities may utilise and produce disaster social social media content.
Abstract: A comprehensive review of online, official, and scientific literature was carried out in 2012-13 to develop a framework of disaster social media. This framework can be used to facilitate the creation of disaster social media tools, the formulation of disaster social media implementation processes, and the scientific study of disaster social media effects. Disaster social media users in the framework include communities, government, individuals, organisations, and media outlets. Fifteen distinct disaster social media uses were identified, ranging from preparing and receiving disaster preparedness information and warnings and signalling and detecting disasters prior to an event to (re)connecting community members following a disaster. The framework illustrates that a variety of entities may utilise and produce disaster social media content. Consequently, disaster social media use can be conceptualised as occurring at a number of levels, even within the same disaster. Suggestions are provided on how the proposed framework can inform future disaster social media development and research.
TL;DR: It is demonstrated that passive Facebook usage undermines affective well-being, and this issue is examined using experimental and field methods.
Abstract: Prior research indicates that Facebook usage predicts declines in subjective well-being over time. How does this come about? We examined this issue in 2 studies using experimental and field methods. In Study 1, cueing people in the laboratory to use Facebook passively (rather than actively) led to declines in affective well-being over time. Study 2 replicated these findings in the field using experience-sampling techniques. It also demonstrated how passive Facebook usage leads to declines in affective well-being: by increasing envy. Critically, the relationship between passive Facebook usage and changes in affective well-being remained significant when controlling for active Facebook use, non-Facebook online social network usage, and direct social interactions, highlighting the specificity of this result. These findings demonstrate that passive Facebook usage undermines affective well-being.
TL;DR: This article inquire into Facebook’s development as a platform by situating it within the transformation of social network sites into social media platforms with a historical perspective on platformization, or the rise of the platform as the dominant infrastructural and economic model of the social web and its consequences.
Abstract: In this article, I inquire into Facebook’s development as a platform by situating it within the transformation of social network sites into social media platforms. I explore this shift with a histo...
TL;DR: Results demonstrate that although Facebook users often experience negative emotions, they feel pressured to access the site frequently due to the fear of missing out and to keep up with relationship maintenance demands, and indicate some methods may not uncover the actual nature or scope of users' experiences.
TL;DR: It is demonstrated how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of cyber hate in a sample of Twitter data.
Abstract: The use of “Big Data” in policy and decision making is a current topic of debate. The 2013 murder of Drummer Lee Rigby in Woolwich, London, UK led to an extensive public reaction on social media, providing the opportunity to study the spread of online hate speech (cyber hate) on Twitter. Human annotated Twitter data was collected in the immediate aftermath of Rigby's murder to train and test a supervised machine learning text classifier that distinguishes between hateful and/or antagonistic responses with a focus on race, ethnicity, or religion; and more general responses. Classification features were derived from the content of each tweet, including grammatical dependencies between words to recognize “othering” phrases, incitement to respond with antagonistic action, and claims of well-founded or justified discrimination against social groups. The results of the classifier were optimal using a combination of probabilistic, rule-based, and spatial-based classifiers with a voted ensemble meta-classifier. We demonstrate how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of cyber hate in a sample of Twitter data. The applications to policy and decision making are discussed.
TL;DR: This research investigates the new stream in e-commerce by proposing a new model to develop understanding of social commerce using a PLS-SEM methodology and results show that Web 2.0 applications are attracting individuals to have interactions as well as generate content on the Internet.
TL;DR: A panorama of the recommender systems in location-based social networks with a balanced depth is presented, facilitating research into this important research theme.
Abstract: Recent advances in localization techniques have fundamentally enhanced social networking services, allowing users to share their locations and location-related contents, such as geo-tagged photos and notes. We refer to these social networks as location-based social networks (LBSNs). Location data bridges the gap between the physical and digital worlds and enables a deeper understanding of users' preferences and behavior. This addition of vast geo-spatial datasets has stimulated research into novel recommender systems that seek to facilitate users' travels and social interactions. In this paper, we offer a systematic review of this research, summarizing the contributions of individual efforts and exploring their relations. We discuss the new properties and challenges that location brings to recommender systems for LBSNs. We present a comprehensive survey analyzing 1) the data source used, 2) the methodology employed to generate a recommendation, and 3) the objective of the recommendation. We propose three taxonomies that partition the recommender systems according to the properties listed above. First, we categorize the recommender systems by the objective of the recommendation, which can include locations, users, activities, or social media. Second, we categorize the recommender systems by the methodologies employed, including content-based, link analysis-based, and collaborative filtering-based methodologies. Third, we categorize the systems by the data sources used, including user profiles, user online histories, and user location histories. For each category, we summarize the goals and contributions of each system and highlight the representative research effort. Further, we provide comparative analysis of the recommender systems within each category. Finally, we discuss the available data-sets and the popular methods used to evaluate the performance of recommender systems. Finally, we point out promising research topics for future work. This article presents a panorama of the recommender systems in location-based social networks with a balanced depth, facilitating research into this important research theme.
TL;DR: This study proposes Twitter as a proxy for human mobility, as it relies on publicly available data and provides high resolution positioning when users opt to geotag their tweets with their current location, and demonstrates that Twitter can be a reliable source for studying human mobility patterns.
Abstract: Understanding human mobility is crucial for a broad range of applications from disease prediction to communication networks. Most efforts on studying human mobility have so far used private and low resolution data, such as call data records. Here, we propose Twitter as a proxy for human mobility, as it relies on publicly available data and provides high resolution positioning when users opt to geotag their tweets with their current location. We analyse a Twitter dataset with more than six million geotagged tweets posted in Australia, and we demonstrate that Twitter can be a reliable source for studying human mobility patterns. Our analysis shows that geotagged tweets can capture rich features of human mobility, such as the diversity of movement orbits among individuals and of movements within and between cities. We also find that short- and long-distance movers both spend most of their time in large metropolitan areas, in contrast with intermediate-distance movers’ movements, reflecting the impact of different modes of travel. Our study provides solid evidence that Twitter can indeed be a useful proxy for tracking and predicting human movement.
TL;DR: This introduction to a special issue of "Telecommunications Policy" entitled "The Governance of Social Media" begins with a definition of social media that informs all contributions in the special issue, and synthesize definitions presented in the literature.
Abstract: This introduction to a special issue of "Telecommunications Policy" entitled "The Governance of Social Media" begins with a definition of social media that informs all contributions in the special issue. A section describing the challenges associated with the governance of social media is presented next, followed by an overview of the various articles included in the special issue.While the Internet and the World Wide Web have always been used to facilitate social interaction, the emergence and rapid diffusion of Web 2.0 functionalities during the first decade of the new millennium enabled an evolutionary leap forward in the social component of web use. This and falling costs for online data storage made it feasible for the first time to offer masses of Internet users access to an array of user-centric spaces they could populate with user-generated content, along with a correspondingly diverse set of opportunities for linking these spaces together to form virtual social networks.To define “social media” for our current purposes, we synthesize definitions presented in the literature and identify the following commonalities among current social media services:1) Social media services are (currently) Web 2.0 Internet-based applications,2) User-generated content is the lifeblood of social media,3) Individuals and groups create user-specific profiles for a site or app designed and maintained by a social media service,4) Social media services facilitate the development of social networks online by connecting a profile with those of other individuals and/or groups.Transformative communication technologies have always called for regulatory innovation. Theodor Vail’s vision of “one policy, one system, universal service” preceded more than one-hundred years of innovative regulations aimed at connecting all Americans to a single telephone network. The sinking of the Titanic, caused in part by “chaos in the spectrum” led to the Radio Act of 1912 and the creation of a command and control model designed to regulate broadcast radio. Safe-harbor hours were put in place after a father and son heard George Carlin’s “seven dirty words” routine over the radio in their car. The fairness doctrine and the minority tax certificate program were designed to address inequalities in the broadcast television industry. The Digital Millennium Copyright Act responded to intellectual property concerns raised by a global Internet and the FCC’s 700mhz auction was the result of demand for smarter mobile phones. Now we must consider the role of regulatory innovation in response to the emergence of social media.
TL;DR: In this article, the authors draw on existing definitions of social media and subcategories from public relations, information technology, and management scholarship, as well as the popular press to develop a definition for social media precise enough to embody these technologies yet robust enough to remain applicable in 2035.
Abstract: What is a social medium, and how may one moderate, isolate, and influence communicative processes within? Although scholars assume an inherent understanding of social media based on extant technology, there is no commonly accepted definition of what social media are, both functionally and theoretically, within communication studies. Given this lack of understanding, cogent theorizing regarding the uses and effects of social media has been limited. This work first draws on extant definitions of social media and subcategories (e.g., social network sites) from public relations, information technology, and management scholarship, as well as the popular press, to develop a definition of social media precise enough to embody these technologies yet robust enough to remain applicable in 2035. It then broadly explores emerging developments in the features, uses, and users of social media for which future theories will need to account. Finally, it divines and prioritizes challenges that may not yet be apparent to t...
TL;DR: A machine learning-based approach to extract mentions of adverse drug reactions (ADRs) from highly informal text in social media, suitable for social media mining, as it relies on large volumes of unlabeled data, thus diminishing the need for large, annotated training data sets.
TL;DR: It is found that the effect of surveillance use of Facebook on depression is mediated by Facebook envy, however, when Facebook envy is controlled for, Facebook use actually lessens depression.
TL;DR: A comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds, and the system architecture of a social media (analytics) platform built by University College London is presented.
Abstract: 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.
TL;DR: In this article, the authors discuss the nature of use of the Internet by American travelers and find that while traditional means of Internet use for travel planning appear to be widespread across all customer segments, higher-order Internet uses are now prevalent among some segments, particularly among travelers of Generation Y.
TL;DR: The results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents.
Abstract: The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories—eg, chemtrails, reptilians or the Illuminati—are pervasive in online social networks (OSN) In this work we study, on a sample of 12 million of individuals, how information related to very distinct narratives—ie main stream scientific and conspiracy news—are consumed and shape communities on Facebook Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents To test potential biases induced by the continued exposure to unsubstantiated rumors on users’ content selection, we conclude our analysis measuring how users respond to 4,709 troll information—ie parodistic and sarcastic imitation of conspiracy theories We find that 7792% of likes and 8086% of comments are from users usually interacting with conspiracy stories
TL;DR: Women high in appearance comparison tendency reported more facial, hair, and skin-related discrepancies after Facebook exposure than exposure to the control website.
Book•
29 Jan 2015
TL;DR: This book presents an overview of the challenges faced by ethnographers who wish to understand activities that involve the internet, and explores both methodological principles and practical strategies for coming to terms with the definition of field sites, the connections between online and offline and the changing nature of embodied experience.
Abstract: The internet has become embedded into our daily lives, no longer an esoteric phenomenon, but instead an unremarkable way of carrying out our interactions with one another. Online and offline are interwoven in everyday experience. Using the internet has become accepted as a way of being present in the world, rather than a means of accessing some discrete virtual domain. Ethnographers of these contemporary Internet-infused societies consequently find themselves facing serious methodological dilemmas: where should they go, what should they do there and how can they acquire robust knowledge about what people do in, through and with the internet?This book presents an overview of the challenges faced by ethnographers who wish to understand activities that involve the internet. Suitable for both new and experienced ethnographers, it explores both methodological principles and practical strategies for coming to terms with the definition of field sites, the connections between online and offline and the changing nature of embodied experience. Examples are drawn from a wide range of settings, including ethnographies of scientific institutions, television, social media and locally based gift-giving networks. - See more at: http://www.bloomsbury.com/uk/ethnography-for-the-internet-9780857855701/#sthash.6wmdZKzF.dpuf
TL;DR: A methodical review of the different approaches to ADR detection/extraction from social media, and their applicability to pharmacovigilance suggests that interest in the utilization of the vast amounts of available social media data for ADR monitoring is increasing.
TL;DR: In this article, the authors examine the influence of comments generated on Facebook on the choice of a hotel and examine the moderator role of Internet users' trust in those comments on these relations.
TL;DR: The authors explores Generation Z, its special relationship with technology and social media, and its values, as well as how this generation may form and practice social interest, and shares recommendations for parents, teachers, and clinicians.
Abstract: The article explores Generation Z, its special relationship with technology and social media, and its values, as well as how this generation may form and practice social interest. The author shares recommendations for parents, teachers, and clinicians.