Matching Items (51)

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Quantifying Invisible Peer Pressure: Social Network Analysis and Peer Influences on Undergraduate Binge Drinking

Description

Binge drinking has clear consequences but subtle influences among undergraduate students. While theories of perceived drinking norms and social identity have been determined to be predictive of binge drinking behavior,

Binge drinking has clear consequences but subtle influences among undergraduate students. While theories of perceived drinking norms and social identity have been determined to be predictive of binge drinking behavior, few studies have tested these influences outside of fraternities, sororities, and athletic teams and little research exists employing social network analysis (SNA) to quantify social ties. In this study, a small, undergraduate dance team was identified to test social identity theory using social network analysis in a peripheral social group. Each member was interviewed for demographic information, personal drinking habits, personal network structure, perceptions of peer drinking within both the personal network and the whole-network (the dance team), and sociometric position within the dance team. Personal network characteristics, whole-network dynamics and perceptions of peer drinking were tested for predictive value of individual binge drinking behavior utilizing binary logistic regression analysis. Results for predictor variables were weakened due to the small sample size (n = 13) and low variability within some constant variables, returning no statistically significant (p < 0.05) independent variables. However, while odds ratios could not be used to construct regression equations, four models were statistically significant overall. Each model was tested again without the constants; no models nor variables were statistically significant. These models indicated, within this sample, that 1) the proportion of a group that adopts binge drinking behavior is predictive of that behavior for the interviewee (in terms of the overall personal network as well as the triads within the personal network); and 2) the perception of the average team member's maximum alcohol intake along with the proportion of the personal network composed of team members is predictive of individual binge drinking behavior. Low variance in the variables and the small sample size warrant further research to test the viability of targeting anti-binge drinking campaigns toward peripheral social groups.

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Agent

Created

Date Created
  • 2017-05

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Analysis of the Aftereffects of Terror Attacks on Social Media

Description

Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that

Social media has become a direct and effective means of transmitting personal opinions into the cyberspace. The use of certain key-words and their connotations in tweets portray a meaning that goes beyond the screen and affects behavior. During terror attacks or worldwide crises, people turn to social media as a means of managing their anxiety, a mechanism of Terror Management Theory (TMT). These opinions have distinct impacts on the emotions that people express both online and offline through both positive and negative sentiments. This paper focuses on using sentiment analysis on twitter hash-tags during five major terrorist attacks that created a significant response on social media, which collectively show the effects that 140-character tweets have on perceptions in social media. The purpose of analyzing the sentiments of tweets after terror attacks allows for the visualization of the effect of key-words and the possibility of manipulation by the use of emotional contagion. Through sentiment analysis, positive, negative and neutral emotions were portrayed in the tweets. The keywords detected also portray characteristics about terror attacks which would allow for future analysis and predictions in regards to propagating a specific emotion on social media during future crisis.

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Created

Date Created
  • 2016-12

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Network Analysis of a Diabetes Prevention Collaboration in Maryvale, Arizona

Description

My aims with this research project were to conduct a network analysis on collaborators in the ¡Viva Maryvale! project, a diabetes prevention program in Maryvale, AZ. The goals of the

My aims with this research project were to conduct a network analysis on collaborators in the ¡Viva Maryvale! project, a diabetes prevention program in Maryvale, AZ. The goals of the social network analysis were to measure the connections that collaborating organizations have to each other, the strength of these connections, and the activities that connected organizations collaborate on. I hypothesized that performing a network analysis would inform me of the strengths and weaknesses of the ¡Viva Maryvale! project in order to advise the next steps of a targeted approach to diabetes prevention among vulnerable populations, thus affecting public health outcomes in the greater Phoenix Valley.

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Agent

Created

Date Created
  • 2017-05

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Predicting Trends on Twitter with Time Series Analysis

Description

Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media.

Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.

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Created

Date Created
  • 2015-05

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A History of Astrobiology: Social Network Structures of the Emerging Field

Description

Astrobiology, as it is known by official statements and agencies, is “the study of the origin, evolution, distribution, and future of life in the universe” (NASA Astrobiology Insitute , 2018).

Astrobiology, as it is known by official statements and agencies, is “the study of the origin, evolution, distribution, and future of life in the universe” (NASA Astrobiology Insitute , 2018). This definition should suit a dictionary, but it may not accurately describe the research and motivations of practicing astrobiologists. Furthermore, it does little to characterize the context in which astrobiologists work. The aim of this project is to explore various social network structures within a large body of astrobiological research, intending to both further define the current motivations of astrobiological research and to lend context to these motivations. In this effort, two Web of Science queries were assembled to search for two contrasting corpora related to astrobiological research. The first search, for astrobiology and its close synonym, exobiology, returned a corpus of 3,229 journal articles. The second search, which includes the first and supplements it with further search terms (see Table 1) returned a corpus of 19,017 journal articles. The metadata for these articles were then used to construct various networks. The resulting networks describe an astrobiology that is well entrenched in other related fields, showcasing the interdisciplinarity of astrobiology in its emergence. The networks also showcase the entrenchment of astrobiology in the sociological context in which it is conducted—namely, its relative dependence on the United States government, which should prompt further discussion amongst astrobiology researchers.

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Created

Date Created
  • 2019-12

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Anonymous social networks versus peer networks in restaurant choice

Description

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.

Contributors

Agent

Created

Date Created
  • 2013

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Resource allocation in communication and social networks

Description

As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to

As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.

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Agent

Created

Date Created
  • 2014