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Results 11 - 20
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573
Cost-Effective Personal Analytics in Social Media Using Language and
"... Limitations to public access of social media, such as increased rate throttling under the re-vised Twitter API, prompts rethinking current approaches for a variety of inference tasks in social networks, such as the prediction of la-tent author attributes. We investigate vari-ous novel network constr ..."
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Limitations to public access of social media, such as increased rate throttling under the re-vised Twitter API, prompts rethinking current approaches for a variety of inference tasks in social networks, such as the prediction of la-tent author attributes. We investigate vari-ous novel network
Real-World Behavior Analysis through a Social Media Lens
"... Abstract. The advent of participatory web has enabled information consumers to become information producers via social media. This phenomenon has attracted researchers of different disciplines including social scientists, political parties, and market researchers to study social media as a source of ..."
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Cited by 10 (4 self)
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of data to explain human behavior in the physical world. Could the traditional approaches of studying social behaviors such as surveys be complemented by computational studies that use massive user-generated data in social media? In this paper, using a large amount of data collected from Twitter
Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages
"... Previous studies have shown that health reports in social media, such as Dai-lyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in par-ticular communities. However, in order for a machine to understand and make in-ferences on th ..."
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Previous studies have shown that health reports in social media, such as Dai-lyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in par-ticular communities. However, in order for a machine to understand and make in-ferences
Combating Threats to Collective Attention in Social Media: An Evaluation
"... Breaking news, viral videos, and popular memes are all examples of the collective attention of huge numbers of users focusing in large-scale social systems. But this selforganization, leading to user attention quickly coalescing and then collectively focusing around a phenomenon, opens these systems ..."
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fold approach. First, we develop data-driven models to simulate large-scale social systems based on parameters derived from a real system. In this way, we can vary parameters – like the fraction of malicious users in the system, their strategies, and the countermeasures available to system operators
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Causal Inference with Rare Events in Large-Scale Time-Series Data
"... Large-scale observational datasets are prevalent in many areas of research, including biomedical informatics, computational social science, and finance. However, our ability to use these data for decision-making lags behind our ability to collect and mine them. One reason for this is the lack of met ..."
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of data available to infer a model of a system’s functioning and evaluates how rare events explain deviations from usual behavior. Using simulated data, we evaluate the approach and compare it against others, demonstrating that it can accurately infer the effects of rare events. 1
Feature-enhanced probabilistic models for diffusion network inference
- In European conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD’12
, 2012
"... Abstract. Cascading processes, such as disease contagion, viral marketing, and information diffusion, are a pervasive phenomenon in many types of networks. The problem of devising intervention strategies to facilitate or inhibit such processes has recently received considerable attention. However, a ..."
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Cited by 8 (0 self)
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, a major challenge is that the underlying network is often unknown. In this paper, we revisit the problem of inferring latent network structure given observations from a diffusion process, such as the spread of trending topics in social media. We define a family of novel probabilistic models that can
A meta-analytic review of obesity prevention programs for children and adolescents: The skinny on interventions that work.
- Psychological Bulletin,
, 2006
"... This meta-analytic review summarizes obesity prevention programs and their effects and investigates participant, intervention, delivery, and design features associated with larger effects. A literature search identified 64 prevention programs seeking to produce weight gain prevention effects, of wh ..."
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Cited by 76 (4 self)
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offered solely to females were more effective than those offered solely to males or those offered to both sexes. We took this approach because (a) this variable emerged as a significant predictor of eating disorder prevention program effects There were also a number of other potential moderators that we
Listening in on Online Conversations: Measuring Brand Sentiment with Social Media
, 2011
"... With the proliferation of social media, questions have begun to emerge about its role in firms ’ marketing research programs. In this research, we investigate the potential to “listen in” on social media conversations as a means of inferring brand sentiment. Our analysis employs data collected from ..."
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With the proliferation of social media, questions have begun to emerge about its role in firms ’ marketing research programs. In this research, we investigate the potential to “listen in” on social media conversations as a means of inferring brand sentiment. Our analysis employs data collected from
Cross-media Cross-genre Information Ranking Multi-media Information Networks
"... Current web technology has brought us a scenario that information about a certain topic is widely dis-persed in data from different domains and data modalities, such as texts and images from news and social media. Automatic extraction of the most informative and important multimedia summary (e.g. a ..."
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Current web technology has brought us a scenario that information about a certain topic is widely dis-persed in data from different domains and data modalities, such as texts and images from news and social media. Automatic extraction of the most informative and important multimedia summary (e.g. a
See What You Want to See: Motivational Influences on Visual Perception,”
- Journal of Personality and Social Psychology,
, 2006
"... People's motivational states-their wishes and preferences-influence their processing of visual stimuli. In 5 studies, participants shown an ambiguous figure (e.g., one that could be seen either as the letter B or the number 13) tended to report seeing the interpretation that assigned them to o ..."
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Cited by 79 (1 self)
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for explaining that we were interested in how their desires could influence the way they saw the figure, 3 for stating they hoped to consume the smoothie, and 3 simply refused to participate when they heard that they might be asked to consume the smoothie. This left data from 63 participants for analysis
Results 11 - 20
of
573
