Emergency Management using Social Networks

doi:10.1109/TENCON.2019.8929699

Citations

PDF

Open Access

More filters

Journal Article•DOI•

An application of media and network multiplexity theory to the structure and perceptions of information environments in hurricane evacuation

[...]

Seungyoon Lee¹, Bailey C. Benedict¹, Yue ‘Gurt’ Ge², Pamela Murray-Tuite³, Satish V. Ukkusuri¹ - Show less +1 more•Institutions (3)

Purdue University¹, University of Central Florida², Clemson University³

01 Jul 2021-Journal of the Association for Information Science and Technology

TL;DR: Survey data collected from households in Jacksonville, Florida affected by 2016's Hurricane Matthew identifies perceived consistency of information as a key predictor of uncertainty regarding hurricane impact and evacuation logistics and provides practical implications regarding the need of information coordination for improved evacuation decision‐making.

...read moreread less

Abstract: Understanding how information use contributes to uncertainties surrounding evacuation decisions is crucial during disasters. While literature increasingly establishes that people consult m...

...read moreread less

7 citations

Cites background from "Emergency Management using Social N..."

...…important to consider the impact of dynamic information environments such as augmented reality tools which assist with realistic visualization of spatial data and social networking sites which allows user-generated updates (Hiltz & Plotnick, 2013; Sharma & Kumar, 2019) on perceived uncertainties....
[...]

References

PDF

Open Access

More filters

{SNAP Datasets}: {Stanford} Large Network Dataset Collection

[...]

Jure Leskovec¹, Andrej Krevl¹•Institutions (1)

Stanford University¹

01 Jun 2014

TL;DR: A collection of more than 50 large network datasets from tens of thousands of node and edges to tens of millions of nodes and edges that includes social networks, web graphs, road networks, internet networks, citation networks, collaboration networks, and communication networks.

...read moreread less

Abstract: A collection of more than 50 large network datasets from tens of thousands of nodes and edges to tens of millions of nodes and edges. In includes social networks, web graphs, road networks, internet networks, citation networks, collaboration networks, and communication networks.

...read moreread less

3,135 citations

"Emergency Management using Social N..." refers background or methods in this paper

...social network, so we used the Facebook dataset provided by Stanford SNAP[18]....
[...]
...Recently a lot of emphasis is on using Twitter data for identifying first stories, due to the fact that Twitter is the most preferred social media because of a large audience [13][17[18]....
[...]
...In this work, we only look at the topological information of social network, so we used the Facebook dataset provided by Stanford SNAP[18]....
[...]
...724 2019 IEEE Region 10 Conference (TENCON 2019) To validate the diffusion model that we propose, we used the Facebook dataset provided by SNAP [30]....
[...]

Journal Article•DOI•

Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth

[...]

Jacob Goldenberg¹, Barak Libai², Eitan Muller³•Institutions (3)

Hebrew University of Jerusalem¹, Technion – Israel Institute of Technology², Tel Aviv University³

01 Aug 2001-Marketing Letters

TL;DR: The results clearly indicate that information dissemination is dominated by both weak and strong w-o-m, rather than by advertising, which means that strong and weak ties become the main forces propelling growth.

...read moreread less

Abstract: Though word-of-mouth (w-o-m) communications is a pervasive and intriguing phenomenon, little is known on its underlying process of personal communications. Moreover as marketers are getting more interested in harnessing the power of w-o-m, for e-business and other net related activities, the effects of the different communications types on macro level marketing is becoming critical. In particular we are interested in the breakdown of the personal communication between closer and stronger communications that are within an individual's own personal group (strong ties) and weaker and less personal communications that an individual makes with a wide set of other acquaintances and colleagues (weak ties). We use a technique borrowed from Complex Systems Analysis called stochastic cellular automata in order to generate data and analyze the results so that answers to our main research issues could be ascertained. The following summarizes the impact of strong and weak ties on the speed of acceptance of a new product: ••The influence of weak ties is at least as strong as the influence of strong ties. Despite the relative inferiority of the weak tie parameter in the model's assumptions, their effect approximates or exceeds that of strong ties, in all stages of the product life cycle. ••External marketing efforts (e.g., advertising) are effective. However, beyond a relatively early stage of the growth cycle of the new product, their efficacy quickly diminishes and strong and weak ties become the main forces propelling growth. The results clearly indicate that information dissemination is dominated by both weak and strong w-o-m, rather than by advertising. ••The effect of strong ties diminishes as personal network size decreases. Market attributes were also found to mediate the effects of weak and strong ties. When personal networks are small, weak ties were found to have a stronger impact on information dissemination than strong ties.

...read moreread less

2,044 citations

Journal Article•DOI•

Inferring friendship network structure by using mobile phone data

[...]

Nathan Eagle¹, Alex Pentland, David Lazer•Institutions (1)

Santa Fe Institute¹

08 Sep 2009-Proceedings of the National Academy of Sciences of the United States of America

TL;DR: It is demonstrated that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns that allow the prediction of individual-level outcomes such as job satisfaction.

...read moreread less

Abstract: Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.

...read moreread less

1,921 citations

"Emergency Management using Social N..." refers methods in this paper

...For this work, they considered three event sequences from Mobile Phone data from a European operator, Reality Mining project [4] and e-mail log from a network....
[...]

Posted Content•

Inferring Networks of Diffusion and Influence

[...]

Manuel Gomez-Rodriguez¹, Jure Leskovec², Andreas Krause³•Institutions (3)

Max Planck Society¹, Stanford University², California Institute of Technology³

01 Jun 2010-arXiv: Data Structures and Algorithms

TL;DR: This work develops an efficient approximation algorithm that scales to large datasets and finds provably near-optimal networks for tracing paths of diffusion and influence through networks and inferring the networks over which contagions propagate.

...read moreread less

Abstract: Information diffusion and virus propagation are fundamental processes taking place in networks. While it is often possible to directly observe when nodes become infected with a virus or adopt the information, observing individual transmissions (i.e., who infects whom, or who influences whom) is typically very difficult. Furthermore, in many applications, the underlying network over which the diffusions and propagations spread is actually unobserved. We tackle these challenges by developing a method for tracing paths of diffusion and influence through networks and inferring the networks over which contagions propagate. Given the times when nodes adopt pieces of information or become infected, we identify the optimal network that best explains the observed infection times. Since the optimization problem is NP-hard to solve exactly, we develop an efficient approximation algorithm that scales to large datasets and finds provably near-optimal networks. We demonstrate the effectiveness of our approach by tracing information diffusion in a set of 170 million blogs and news articles over a one year period to infer how information flows through the online media space. We find that the diffusion network of news for the top 1,000 media sites and blogs tends to have a core-periphery structure with a small set of core media sites that diffuse information to the rest of the Web. These sites tend to have stable circles of influence with more general news media sites acting as connectors between them.

...read moreread less

915 citations

"Emergency Management using Social N..." refers background in this paper

...Explanatory Models: Gomez et al.[8] propose a model over static networks that tries to reconstruct the edges of a diffusion network by observing the timing of node infection over multiple information cascades and also propose a NETINF model to infer this diffusion network....
[...]
...They extend this idea [8] over static networks to propose NETRATE [20] that models the diffusion network as comprising of spatially discrete sets of diffusion networks....
[...]

Journal Article•DOI•

Information diffusion in online social networks: a survey

[...]

Adrien Guille, Hakim Hacid¹, Cécile Favre, Djamel A. Zighed•Institutions (1)

Bell Labs¹

16 Jul 2013

TL;DR: A survey of representative methods dealing with information diffusion in social networks and a taxonomy that summarizes the state-of-the-art is proposed, intended to help researchers in quickly understanding existing works and possible improvements to bring.

...read moreread less

Abstract: Online social networks play a major role in the spread of information at very large scale. A lot of effort have been made in order to understand this phenomenon, ranging from popular topic detection to information diffusion modeling, including influential spreaders identification. In this article, we present a survey of representative methods dealing with these issues and propose a taxonomy that summarizes the state-of-the-art. The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks. This survey is intended to help researchers in quickly understanding existing works and possible improvements to bring.

...read moreread less

823 citations

"Emergency Management using Social N..." refers background or methods in this paper

...Other Predictive Models were based on the assumption of a static network; hence, they would not function well on realworld social networks that are dynamic in nature....
[...]
...Information Diffusion Modelling: In trying to model information diffusion on social networks, two kinds of approaches can be undertaken, namely Explanatory Models and Predictive Models [11]....
[...]
...Much work has been done towards using social media data to identify posts about a crisis or disaster and formalizing them into a structure to help the authorities or layman [13][28][22][11]....
[...]
...Predictive Models: Linear Threshold Model and Independent Cascade models are the models that have been the underlying models of various predictive models of Information diffusion on Social Networks and have been discussed in brief below [17]....
[...]

Collapse

Emergency Management using Social Networks

Citations

Cites background from "Emergency Management using Social N..."

References

"Emergency Management using Social N..." refers background or methods in this paper

"Emergency Management using Social N..." refers methods in this paper

"Emergency Management using Social N..." refers background in this paper

"Emergency Management using Social N..." refers background or methods in this paper

Related Papers (5)