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Dynamical Classes of Collective Attention in Twitter
[article]
2012
arXiv
pre-print
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Here we focus on spikes of collective attention in Twitter, and specifically on peaks in the popularity of hashtags. ...
We link these dynamical classes to the events the hashtags represent and use text mining techniques to provide a semantic characterization of the hastag classes. ...
JJR acknowledges support from the JAE program of the CSIC and from the Spanish Ministry of Science (MICINN) through the project MODASS (FIS2011-24785). ...
arXiv:1111.1896v2
fatcat:w4mjh7gf6zghdophnrov2rawue
Dynamical classes of collective attention in twitter
2012
Proceedings of the 21st international conference on World Wide Web - WWW '12
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Here we focus on spikes of collective attention in Twitter, and specifically on peaks in the popularity of hashtags. ...
We link these dynamical classes to the events the hashtags represent and use text mining techniques to provide a semantic characterization of the hashtag classes. ...
In Section 4 we identify dynamical classes of hashtag usage and relate them to the semantics of the corresponding tweets. ...
doi:10.1145/2187836.2187871
dblp:conf/www/LehmannGRC12
fatcat:6ywauhfowzcapf2xysfzidfwv4
Credibility and Dynamics of Collective Attention
[article]
2016
arXiv
pre-print
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Here we ask: How do the dynamics of collective attention directed toward an event reported on social media vary with its perceived credibility? ...
In other words, as more people showed interest during moments of transient collective attention, the associated uncertainty surrounding these events also increased. ...
Another parallel study focusing on spikes of collective attention in Twitter, analyzed the popularity peaks of Twitter hashtags [23] . ...
arXiv:1612.08440v1
fatcat:a2dd6pstzjbevmhd3mrvpyavb4
Credibility and the Dynamics of Collective Attention
2017
Proceedings of the ACM on Human-Computer Interaction
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Here we ask: How do the dynamics of collective attention directed toward an event reported on social media vary with its perceived credibility? ...
In other words, as more people showed interest during moments of transient collective attention, the associated uncertainty surrounding these events also increased. ...
Another parallel study focusing on spikes of collective attention in Twitter, analyzed the popularity peaks of Twitter hashtags [24] . ...
doi:10.1145/3134715
fatcat:aqtl2dnnivbtfn55lw4gtyjkt4
A Dynamical Model of Twitter Activity Profiles
2015
Proceedings of the 26th ACM Conference on Hypertext & Social Media - HT '15
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We look into Twitter to understand the dynamics behind the users' posting activities---tweets and retweets---zooming in on topics that peaked in popularity. ...
Furthermore, we introduce an alternative in classifying the collective activities on the socio-technical system based on the model. ...
Particularly, we investigate the observations described in [14] on the dynamical classes of collective attention in Twitter where they defined four groups depending on the temporal features of their ...
doi:10.1145/2700171.2791029
dblp:conf/ht/HuynhLM15
fatcat:2xmxwbpqbjgjtmhf3aiwkag3s4
Contagion dynamics of extremist propaganda in social networks
[article]
2017
arXiv
pre-print
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Recent terrorist attacks carried out on behalf of ISIS on American and European soil by lone wolf attackers or sleeper cells remind us of the importance of understanding the dynamics of radicalization ...
In this paper, we shed light on the social media activity of a group of twenty-five thousand users whose association with ISIS online radical propaganda has been manually verified. ...
Government had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The U.S. ...
arXiv:1701.08170v2
fatcat:csqjwrvqtjgwfdgolxhrokeqsi
Mining and comparing engagement dynamics across multiple social media platforms
2014
Proceedings of the 2014 ACM conference on Web science - WebSci '14
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In this paper we define a common framework of engagement analysis and examine and compare engagement dynamics across five social media platforms: Facebook, Twitter, Boards.ie, Stack Overflow and the SAP ...
To date, many pieces of work have examined engagement dynamics in isolated platforms with little consideration or assessment of how these dynamics might vary between disparate social media systems. ...
The role of topics in attention generation were also investigated. ...
doi:10.1145/2615569.2615677
dblp:conf/websci/RoweA14
fatcat:qhhbxpheyzagfnddxjo2w44uv4
Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties
2015
PLoS ONE
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Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media. ...
In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information ...
the "noise" in the dynamics of collective attention in social media. ...
doi:10.1371/journal.pone.0131184
pmid:26161795
pmcid:PMC4498694
fatcat:3ulpndwumrgprg3mppiwyxpzju
Evolution of online user behavior during a social upheaval
2014
Proceedings of the 2014 ACM conference on Web science - WebSci '14
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2014 pre-print arXiv:1406.7197v1 fatcat:4dpstbif6nemtmrynlchrbisju
Here we present a study of the Gezi Park movement in Turkey through the lens of Twitter. We analyze over 2.3 million tweets produced during the 25 days of protest occurred between May and June 2013. ...
We first characterize the spatio-temporal nature of the conversation about the Gezi Park demonstrations, showing that similarity in trends of discussion mirrors geographic cues. ...
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ...
doi:10.1145/2615569.2615699
dblp:conf/websci/VarolFOMF14
fatcat:vw2qje2vwvedjhyp3fvuup5xka
A Hybrid Classification Algorithm to Classify Engineering Students Problems and Perks
2016
International Journal of Data Mining & Knowledge Management Process
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The large and growing scale of information needs automatic classification techniques. Sentiment analysis is one of the automated techniques to classify large data. ...
The social networking sites have brought a new horizon for expressing views and opinions of individuals. ...
In our study, we have collected data from Twitter that has witnessed a tremendous growth in the number of users recently [8] [9] . ...
doi:10.5121/ijdkp.2016.6206
fatcat:6rqtedx72ja4dldfsocuxkwmcq
How Visibility and Divided Attention Constrain Social Contagion
2012
2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing
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2012 pre-print arXiv:1205.2736v1 fatcat:qirhgu6knffxbloctk6zkpv2qmOther Versions
Researchers have recently examined a number of factors that affect information diffusion in online social networks, including: the novelty of information, users' activity levels, who they pay attention ...
Using URLs as markers of information, we carry out a detailed study of retweeting, the primary mechanism by which information spreads on the Twitter follower graph. ...
Analyzing this human response dynamic allows us to observe how users manage the inherently dynamic nature of the twitter queue. ...
doi:10.1109/socialcom-passat.2012.129
dblp:conf/socialcom/HodasL12
fatcat:ehu7hcq5evhyrprgeghekhjs2u
Attention Inequality in Social Media
[article]
2016
arXiv
pre-print
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In this paper, we examine the distribution of attention across a large sample of users of a popular social media site Twitter. ...
We develop a phenomenological model that quantifies attention diffusion and network dynamics, and solve it to study how attention inequality grows over time in a dynamic environment of social media. ...
Attention Diffusion Model To help explain dynamics of attention inequality in online social media, we develop a model of network dynamics via diffusion of attention. ...
arXiv:1601.07200v1
fatcat:hgqde36airgczp3ss5zsepk55q
Choice of Best Samples for Building Ensembles in Dynamic Environments
[chapter]
2016
Communications in Computer and Information Science
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In this work, we propose a technique to define the best set of training examples using dynamic ensembles in text classification scenarios. ...
In dynamic environments, where new data is constantly appearing, old data is usually disregarded, but sometimes some of those disregarded examples may carry substantial information. ...
In this section we presented some examples of the importance of tackling drift in dynamic scenarios like social networks, and particularly in Twitter. ...
doi:10.1007/978-3-319-44188-7_3
fatcat:clewj6mwrvbnlb5sg6cccf75dq
A Prediction of Twitter Sentiment Class using Bi-directional Long Short Term Memory with Self-Attention Layer Mechanism
2020
International Journal of Advanced Trends in Computer Science and Engineering
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In recent decade, the sentimental analysis using twitter data gained more attention among the researchers. ...
Initially, the input data was collected from Sanders Twitter Corpus (STC) dataset. ...
In this work, the source data is collected from twitter for analyzing the people sentiments. ...
doi:10.30534/ijatcse/2020/04952020
fatcat:m4dnuyiamzeidcgto3km2ctage
Unraveling the Origin of Social Bursts in Collective Attention
[article]
2019
arXiv
pre-print
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In fact, the complex interplay between individual and social activities in social systems overwhelmed by information results in bursty activity of collective attention which are still poorly understood ...
We observe extreme fluctuations in collective attention that we are able to characterize and explain by considering the co-occurrence of two fundamental factors: the heterogeneity of social interactions ...
Analysis of bursty activity due to collective attention. Let us focus our attention on the evolution of collective attention dynamics over time, during different special events, shown in Fig. 1 . ...
arXiv:1903.06588v1
fatcat:2je6dav24jgpddvofsywomwsiu
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