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Subject = Twitter;
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Displaying Results 1 - 25 of 29 on page 1 of 2
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‘Hacking multitude’ and Big Data: Some insights from the Turkish ‘digital coup’
(2015)
Cardullo, Paolo
‘Hacking multitude’ and Big Data: Some insights from the Turkish ‘digital coup’
(2015)
Cardullo, Paolo
Abstract:
The paper presents my first findings and reflections on how ordinary people may opportunistically and unpredictably respond to Internet censorship and tracking. I try to capture this process with the concept of ‘hacking multitude'. Working on a case study of the Turkish government's block of the social media platform Twitter (March 2014), I argue that during systemic data choke-points, a multitude of users might acquire a certain degree of reflexivity over ubiquitous software of advanced techno-capitalism. Resisting naïve parallels between urban streets and virtual global streets, the article draws on Fuller's ‘media ecologies' to make sense of complex and dynamic interactions between processes and materialities, strategies of communication and mundane practices. Such a dense space is mostly invisible to network and traffic analysis, although it comes alive under the magnifying lens of digital ethnography. As the Turkish government tried to stop protesters on bot...
http://mural.maynoothuniversity.ie/9335/
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#hardtoparse: POS tagging and parsing the twitterverse
(2011)
Foster, Jennifer; Cetinoglu, Ozlem; Wagner, Joachim; Le Roux, Joseph; Hogan, Stephen; N...
#hardtoparse: POS tagging and parsing the twitterverse
(2011)
Foster, Jennifer; Cetinoglu, Ozlem; Wagner, Joachim; Le Roux, Joseph; Hogan, Stephen; Nivre, Joakim; Hogan, Deirdre; van Genabith, Josef
Abstract:
We evaluate the statistical dependency parser, Malt, on a new dataset of sentences taken from tweets. We use a version of Malt which is trained on gold standard phrase structure Wall Street Journal (WSJ) trees converted to Stanford labelled dependencies. We observe a drastic drop in performance moving from our in-domain WSJ test set to the new Twitter dataset, much of which has to do with the propagation of part-of-speech tagging errors. Retraining Malt on dependency trees produced by a state-of-the-art phrase structure parser, which has itself been self-trained on Twitter material, results in a significant improvement. We analyse this improvement by examining in detail the effect of the retraining on individual dependency types.
http://doras.dcu.ie/16484/
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An analysis of interactions within and between extreme right communities in social media
(2012)
O'Callaghan, Derek; Greene, Derek; Conway, Maura; Carthy, Joe; Cunningham, Padraig
An analysis of interactions within and between extreme right communities in social media
(2012)
O'Callaghan, Derek; Greene, Derek; Conway, Maura; Carthy, Joe; Cunningham, Padraig
Abstract:
Many extreme right groups have had an online presence for some time through the use of dedicated websites. This has been accompanied by increased activity in social media websites in recent years, which may enable the dissemination of extreme right content to a wider audience. In this paper, we present exploratory analysis of the activity of a selection of such groups on Twitter, using network representations based on reciprocal follower and mentions interactions. We find that stable communities of related users are present within individual country networks, where these communities are usually associated with variants of extreme right ideology. Furthermore, we also identify the presence of international relationships between certain groups across geopolitical boundaries.
http://doras.dcu.ie/17746/
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An investigation of term weighting approaches for microblog retrieval
(2012)
Ferguson, Paul; O'Hare, Neil; Lanagan, James; Phelan, Owen; McCarthy, Kevin
An investigation of term weighting approaches for microblog retrieval
(2012)
Ferguson, Paul; O'Hare, Neil; Lanagan, James; Phelan, Owen; McCarthy, Kevin
Abstract:
The use of effective term frequency weighting and docu- ment length normalisation strategies have been shown over a number of decades to have a significant positive effect for document retrieval. When dealing with much shorter documents, such as those obtained from mi- croblogs, it would seem intuitive that these would have less benefit. In this paper we investigate their effect on microblog retrieval performance using the Tweets2011 collection from the TREC 2011 Microblog Track.
http://doras.dcu.ie/16788/
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Big course small talk: twitter and MOOCs: a systematic review of research designs 2011–2017
(2018)
Costello, Eamon; Browne, Mark; Nic Giolla Mhichíl, Mairéad; Zhang, Jingjing
Big course small talk: twitter and MOOCs: a systematic review of research designs 2011–2017
(2018)
Costello, Eamon; Browne, Mark; Nic Giolla Mhichíl, Mairéad; Zhang, Jingjing
Abstract:
Although research on the use of Twitter in support of learning and teaching has become an established field of study the role of Twitter in the context of Massive Open Online Courses (MOOCs) has not yet been adequately considered and specifically in the literature. Accordingly, this paper addresses a number of gaps in the scholarly interface between Twitter and MOOCs by undertaking a comprehensive mapping of the current literature. In so doing the paper examines research design through: data collection and analysis techniques; scope and scale of existing studies; and theoretical approaches and underpinnings in the empirical research published between 2011 and 2017. Findings serve to demonstrate the diversity of this line of research, particularly in scale and scope of studies and in the approaches taken. By mapping the research using a systematic review methodology it is shown that there is a lack of qualitative data on how Twitter is used by learners and teachers in MOOCs. Moreover...
http://doras.dcu.ie/23085/
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CLARITY at the TREC 2011 microblog track
(2011)
Ferguson, Paul; O'Hare, Neil; Lanagan, James; Smeaton, Alan F.; Phelan, Owen; McCa...
CLARITY at the TREC 2011 microblog track
(2011)
Ferguson, Paul; O'Hare, Neil; Lanagan, James; Smeaton, Alan F.; Phelan, Owen; McCarthy, Kevin; Smyth, Barry
Abstract:
For the first year of the TREC Microblog Track the CLARITY group concentrated on a number of areas, investigating the underlying term weighting scheme for ranking tweets, incorporating query expansion to introduce new terms into the query, as well as introducing an element of temporal re-weighting based on the temporal distribution of assumed relevant microblogs.
http://doras.dcu.ie/16789/
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Code-switching in Irish tweets: a preliminary analysis
(2019)
Lynn, Teresa; Scannell, Kevin
Code-switching in Irish tweets: a preliminary analysis
(2019)
Lynn, Teresa; Scannell, Kevin
Abstract:
As is the case with many languages, research into code-switching in Modern Irish has, until recently, mainly been focused on the spoken language. Online usergenerated content (UGC) is less restrictive than traditional written text, allowing for code-switching, and as such, provides a new platform for text-based research in this field of study. This paper reports on the annotation of (English) code-switching in a corpus of 1496 Irish tweets and provides a computational analysis of the nature of code-switching amongst Irish speaking Twitter users, with a view to providing a basis for future linguistic and socio-linguistic studies.
http://doras.dcu.ie/23598/
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DCU-ADAPT: Learning edit operations for microblog normalisation with the generalised perceptron
(2015)
Wagner, Joachim; Foster, Jennifer
DCU-ADAPT: Learning edit operations for microblog normalisation with the generalised perceptron
(2015)
Wagner, Joachim; Foster, Jennifer
Abstract:
We describe the work carried out by the DCU-ADAPT team on the Lexical Normalisation shared task at W-NUT 2015. We train a generalised perceptron to annotate noisy text with edit operations that normalise the text when executed. Features are character n-grams, recurrent neural network language model hidden layer activations, character class and eligibility for editing according to the task rules. We combine predictions from 25 models trained on subsets of the training data by selecting the most-likely normalisation according to a character language model. We compare the use of a generalised perceptron to the use of conditional random fields restricted to smaller amounts of training data due to memory constraints. Furthermore, we make a first attempt to verify Chrupała (2014)’s hypothesis that the noisy channel model would not be useful due to the limited amount of training data for the source language model, i.e. the language model on normalised text.
http://doras.dcu.ie/20694/
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Determining the role of the Internet in violent extremism and terrorism: six suggestions for progressing research
(2016)
Conway, Maura
Determining the role of the Internet in violent extremism and terrorism: six suggestions for progressing research
(2016)
Conway, Maura
Abstract:
Some scholars and others are skeptical of a significant role for the Internet in processes of violent radicalization. There is increasing concern on the part of other scholars, and increasingly also policymakers and publics, that easy availability of violent extremist content online may have violent radicalizing effects. This article identifies a number of core questions regarding the interaction of violent extremism and terrorism and the Internet, particularly social media, that have yet to be adequately addressed and supplies a series of six follow-up suggestions, flowing from these questions, for progressing research in this area. These suggestions relate to (1) widening the range of types of violent online extremism being studied beyond violent jihadis; (2) engaging in more comparative research, not just across ideologies, but also groups, countries, languages, and social media platforms; (3) deepening our analyses to include interviewing and virtual ethnographic approaches; (4)...
http://doras.dcu.ie/21238/
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Disrupting Daesh: measuring takedown of online terrorist material and it's impacts
(2017)
Conway, Maura; Khawaja, Moign; Lakhani, Suraj; Reffin, Jeremy; Robertson, Andrew; Weir,...
Disrupting Daesh: measuring takedown of online terrorist material and it's impacts
(2017)
Conway, Maura; Khawaja, Moign; Lakhani, Suraj; Reffin, Jeremy; Robertson, Andrew; Weir, David
Abstract:
This report seeks to contribute to public and policy debates on the value of social media disruption activity with respect to terrorist material. We look in particular at aggressive account and content takedown, with the aim of accurately measuring this activity and its impacts. Our findings challenge the notion that Twitter remains a conducive space for Islamic State (IS) accounts and communities to flourish, although IS continues to distribute propaganda through this channel. However, not all jihadists on Twitter are subject to the same high levels of disruption as IS, and we show that there is differential disruption taking place. IS’s and other jihadists’ online activity was never solely restricted to Twitter. Twitter is just one node in a wider jihadist social media ecology. We describe and discuss this, and supply some preliminary analysis of disruption trends in this area.
http://doras.dcu.ie/21961/
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Elections and political communication
(2014)
Ó Beacháin, Donnacha
Elections and political communication
(2014)
Ó Beacháin, Donnacha
http://doras.dcu.ie/24182/
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Mark
Feeling anxious? Perceiving anxiety in tweets using machine learning
(2019)
Gruda, Jon; Hasan, Souleiman
Feeling anxious? Perceiving anxiety in tweets using machine learning
(2019)
Gruda, Jon; Hasan, Souleiman
Abstract:
This study provides a predictive measurement tool to examine perceived anxiety from a longitudinal perspective, using a non-intrusive machine learning approach to scale human rating of anxiety in microblogs. Results suggest that our chosen machine learning approach depicts perceived user state-anxiety fluctuations over time, as well as mean trait anxiety. We further find a reverse relationship between perceived anxiety and outcomes such as social engagement and popularity. Implications on the individual, organizational, and societal levels are discussed.
http://mural.maynoothuniversity.ie/11261/
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From news to comment: Resources and benchmarks for parsing the language of web 2.0
(2011)
Foster, Jennifer; Cetinoglu, Ozlem; Wagner, Joachim; Le Roux, Joseph; Nivre, Joakim; Ho...
From news to comment: Resources and benchmarks for parsing the language of web 2.0
(2011)
Foster, Jennifer; Cetinoglu, Ozlem; Wagner, Joachim; Le Roux, Joseph; Nivre, Joakim; Hogan, Deirdre; van Genabith, Josef
Abstract:
We investigate the problem of parsing the noisy language of social media. We evaluate four all-Street-Journal-trained statistical parsers (Berkeley, Brown, Malt and MST) on a new dataset containing 1,000 phrase structure trees for sentences from microblogs (tweets) and discussion forum posts. We compare the four parsers on their ability to produce Stanford dependencies for these Web 2.0 sentences. We find that the parsers have a particular problem with tweets and that a substantial part of this problem is related to POS tagging accuracy. We attempt three retraining experiments involving Malt, Brown and an in-house Berkeley-style parser and obtain a statistically significant improvement for all three parsers.
http://doras.dcu.ie/16854/
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From smart cities to smart neighborhoods: detecting local events from social media
(2014)
Li, Yang; Smeaton, Alan F.
From smart cities to smart neighborhoods: detecting local events from social media
(2014)
Li, Yang; Smeaton, Alan F.
Abstract:
There are several examples of work which uses data from so- cial media to detect events which occur in our real, physical world. Our target for event detection is to partition a large geographic region, a whole city in our case, into smaller districts based on geotagged Tweets and to detect smaller local events. We generate a language model for Tweets from each district and measure the KL divergence on incoming Tweets to detect outliers. When these reach a sizable volume or intensity and are consistent, this indicates an event within that district. We used Tweets drawn from Dublin city and we describe experiments on partitioning the city into districts and detecting local events within districts.
http://doras.dcu.ie/19919/
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How Journalists Source Trending Social Media Feeds
(2019)
Bouvier, Gwen
How Journalists Source Trending Social Media Feeds
(2019)
Bouvier, Gwen
Abstract:
Media scholars have called for more research to understand the consequences of news outlets becoming increasingly reliant on social media for sourcing stories, and how this is changing the nature of news and the role of the journalist. This also has high relevance for the Critical Discourse Analyst as regards processes of attributing the nature of ideology, where there is a shift away from stories derived from elite sources and official organizations. Using a sample of 26 news stories and a corpus of 40,000 tweets from a feed called #twowomentravel, which dealt with the journey of two women travelling from Ireland to the United Kingdom for an abortion, this paper uses Multimodal Critical Discourse Analysis to investigate how the discourses from the feed are taken up by the journalists. Findings show an erosion of some of the basic former aspects of journalistic practice related to verification and provision of context as what is “trending” becomes a news definer. Yet those with the ...
http://mural.maynoothuniversity.ie/11870/
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Introduction: #SocialmediaShakespeares
(2016)
Calbi, Maurizio; O'Neill, Stephen
Introduction: #SocialmediaShakespeares
(2016)
Calbi, Maurizio; O'Neill, Stephen
Abstract:
In their introductory essay, Maurizio Calbi and Stephen O'Neill explore the interrelations between social media and Shakespeare(s), providing a theoretical consideration of both categories that ultimately moves toward an argument for their rhizomatic intersections. Shakespeare increasingly "becomes" through social media (in a Deleuzian sense), and indeed, forms of social media are rearticulated through Shakespeare. The essay also guides the reader through this special issue in which the contributors variously map, define, scrutinize, and challenge social media, Shakespeare and their uncanny convergences.
http://mural.maynoothuniversity.ie/11453/
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Online social media in the Syria conflict: encompassing the extremes and the in-betweens
(2014)
O'Callaghan, Derek; Prucha, Nico; Greene, Derek; Conway, Maura; Cunningham, Padrai...
Online social media in the Syria conflict: encompassing the extremes and the in-betweens
(2014)
O'Callaghan, Derek; Prucha, Nico; Greene, Derek; Conway, Maura; Cunningham, Padraig; Carthy, Joe
Abstract:
The Syria conflict has been described as the most socially mediated in history, with online social media playing a particularly important role. At the same time, the ever-changing landscape of the conflict leads to difficulties in applying analytical approaches taken by other studies of online political activism. Therefore, in this paper, we use an approach that does not require strong prior assumptions or the proposal of an advance hypothesis to analyze Twitter and YouTube activity of a range of protagonists to the conflict, in an attempt to reveal additional insights into the relationships between them. By means of a network representation that combines multiple data views, we uncover communities of accounts falling into four categories that broadly reflect the situation on the ground in Syria. A detailed analysis of selected communities within the anti-regime categories is provided, focusing on their central actors, preferred online platforms, and activity surrounding “real world...
http://doras.dcu.ie/20485/
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Public networked discourses in the Ukraine-Russia conflict: ‘patriotic hackers’ and digital populism
(2017)
Lokot, Tetyana
Public networked discourses in the Ukraine-Russia conflict: ‘patriotic hackers’ and digital populism
(2017)
Lokot, Tetyana
Abstract:
This paper explores the self-presentation and online discursive practices of grass- roots hacker collectives on both sides of the Ukraine-Russia conflict within a larger geopolitical climate of a contested globalisation agenda and a growing fear of cyber warfare. Both pro-Russian and pro-Ukrainian hacker groups engage in DDoS attacks, malware distribution and leaking stolen information from the opposing side. They also use social media to enter the broader political discourse around the conflict. The paper analyses the Twitter posts of both collectives to reveal key modes of online practices and key discursive themes in the context of the conflict, such as political activism, information warfare, hacker ethics and patriotism. The study elucidates how these groups use their social media presence to construct a ‘patriotic hacker’ identity for themselves, to delegitimise their opponents and ultimately, to connect to the broader populist dis- course, where issues of patriotism, sovereig...
http://doras.dcu.ie/23185/
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Research ethics of Twitter for MOOCs
(2019)
Costello, Eamon; Donlon, Enda; Brown, Mark
Research ethics of Twitter for MOOCs
(2019)
Costello, Eamon; Donlon, Enda; Brown, Mark
Abstract:
This study examined the ethical considerations researchers have made when investigating MOOC learners’ and teachers’ Twitter activity. In so doing, it sought to addresses the lack of an evidencebased understanding of the ethical implications of research into Twitter as a site of teaching and learning. Through an analysis of 31 studies, we present a mapping of the ethical practices of researchers in this area. We identified potential ethical issues and concerns that have arisen. Our main contribution is to seek to challenge researchers to engage critically with ethical issues and, hence, develop their own understanding of ethically appropriate approaches. To this end, we also reflected and reported on our own evolving practice.
http://doras.dcu.ie/23773/
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Russian Twitter disinformation campaigns reach across the American political spectrum
(2020)
Freelon, Deen; Lokot, Tetyana
Russian Twitter disinformation campaigns reach across the American political spectrum
(2020)
Freelon, Deen; Lokot, Tetyana
Abstract:
Evidence from an analysis of Twitter data reveals that Russian social media trolls exploited racial and political identities to infiltrate distinct groups of authentic users, playing on their group identities. The groups affected spanned the ideological spectrum, suggesting the importance of coordinated counter-responses from diverse coalitions of users.
http://doras.dcu.ie/24154/
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Sentiment analysis and real-time microblog search
(2012)
Bermingham, Adam
Sentiment analysis and real-time microblog search
(2012)
Bermingham, Adam
Abstract:
This thesis sets out to examine the role played by sentiment in real-time microblog search. The recent prominence of the real-time web is proving both challenging and disruptive for a number of areas of research, notably information retrieval and web data mining. User-generated content on the real-time web is perhaps best epitomised by content on microblogging platforms, such as Twitter. Given the substantial quantity of microblog posts that may be relevant to a user query at a given point in time, automated methods are required to enable users to sift through this information. As an area of research reaching maturity, sentiment analysis offers a promising direction for modelling the text content in microblog streams. In this thesis we review the real-time web as a new area of focus for sentiment analysis, with a specific focus on microblogging. We propose a system and method for evaluating the effect of sentiment on perceived search quality in real-time microblog search scenarios. ...
http://doras.dcu.ie/16748/
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Social media #MOOC mentions: lessons for MOOC research from analysis of Twitter data
(2016)
Costello, Eamon; Nair, Binesh; Brown, Mark; Zhang, Jingjing; Nic Giolla Mhichíl, Mairéa...
Social media #MOOC mentions: lessons for MOOC research from analysis of Twitter data
(2016)
Costello, Eamon; Nair, Binesh; Brown, Mark; Zhang, Jingjing; Nic Giolla Mhichíl, Mairéad; Donlon, Enda; Lynn, Theo
Abstract:
There is a relative dearth of research into what is being said about MOOCs by users in social media, particularly through analysis of large datasets. In this paper we contribute to addressing this gap through an exploratory analysis of a Twitter dataset. We present an analysis of a dataset of tweets that contain the hashtag #MOOC. A three month sample of tweets from the global Twitter stream was obtained using the GNIP API. Using techniques for analysis of large microblogging datasets we conducted descriptive analysis and content analysis of the data. Our findings suggest that the set of tweets containing the hashtag #MOOC has some strong characteristics of an information network. Course providers and platforms are prominent in the data but teachers and learners are also evident. We draw lessons for further research based on our findings.
http://doras.dcu.ie/21716/
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Social Media and Its Impact on Intercultural Communication: The Challenges for a Discourse Approach
(2016)
Bouvier, Gwen
Social Media and Its Impact on Intercultural Communication: The Challenges for a Discourse Approach
(2016)
Bouvier, Gwen
Abstract:
The wider field of discourse studies is still only beginning to turn its attention to social media, despite a number of notable scholarly works. This paper looks at some of the challenges for a discourse approach to multicultural communication on social media. It sees the global communication landscape as fundamentally transformed and shifted in the ways in which identities and communities play out. The paper concludes by thinking about what the consequence of these are, specifically the way identity is negotiated online, how cross-cultural debate pans out, how the status of knowledge is changing, and the relationship between the online and offline world. The challenge for discourse studies is to create more robust research and studies that provide concrete examples of these changes.
http://mural.maynoothuniversity.ie/11871/
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Social media and political communication
(2014)
Molony, Martin
Social media and political communication
(2014)
Molony, Martin
http://doras.dcu.ie/24179/
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Teaching Twitter: Re-enacting the Paris Commune and the Battle of Stalingrad
(2014)
McKenzie, Brian A.
Teaching Twitter: Re-enacting the Paris Commune and the Battle of Stalingrad
(2014)
McKenzie, Brian A.
Abstract:
Abstract included in text.
http://mural.maynoothuniversity.ie/7027/
Displaying Results 1 - 25 of 29 on page 1 of 2
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