Extracting Knowledge from the Geometric Shape of Social Network Data Using Topological Data Analysis

Almgren, Khaled; Kim, Minkyu; Lee, Jeong-Kyu

doi:10.3390/e19070360

Cited by 13 publications

(10 citation statements)

References 42 publications

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“…In addition, their study investigates the feasibility of topological data analysis for social media mining. In addition, their study showed that the shape of data can produce meaningful information [37]. This approach can be useful in analysing visual images in the media, but, as mentioned in the Introduction, our study concerned more about text as a unit of analysis.…”

Section: Graph Theorymentioning

confidence: 99%

“…To formulate the theoretical framework, research problem and its further consequences, this study suggests the algorithm in Figure 6. most recent study conducted topological data analysis to analyse social media to predict the popularity of images in the data [37]. In addition, their study investigates the feasibility of topological data analysis for social media mining.…”

Section: Algorithm Of Theoretical Frameworkmentioning

confidence: 99%

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Semantic Network Analysis of Legacy News Media Perception in South Korea: The Case of PyeongChang 2018

Yoon

Chung

2018

Sustainability

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This paper aims at exploring how conservative and liberal newspapers in South Korea framed PyeongChang 2018 directly. Our research questions addressed four points: first, different attitudes of conservative and liberal newspapers in the PyeongChang news reporting; second, their success and failure in influencing public opinion; third, South Koreans’ perceptions on PyeongChang 2018; and fourth, South Korean public reliance on the newspapers. To investigate the framing differences, we employed a big data analytic method (automated semantic network analysis) with NodeXL (analytic software). Conclusively, we were able to find out four main findings. First, the conservative media showed pessimistic attitudes to the Olympics, and the liberal media did conversely. Second, despite the conservative media’s resourcefulness, they could not succeed in influencing public opinion. Third, the conservative media perceived the Olympics as an undesirable event, but the liberal media did the Olympics as a significant event for further peace promotion. Fourth, the conservative media’s framings did not considerably influence upon the public opinion. As a conclusion, the public are no longer passive recipients of the messages from the media. Instead, they tend to selectively accept the information from the media based on ‘collective intelligence’. This trend provides a significant implication for enhancing the sustainability of the media environment in South Korea.

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Section: Graph Theorymentioning

confidence: 99%

Section: Algorithm Of Theoretical Frameworkmentioning

confidence: 99%

Semantic Network Analysis of Legacy News Media Perception in South Korea: The Case of PyeongChang 2018

Yoon

Chung

2018

Sustainability

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“…They reported a monotonic increase in the ratio of popularity over the cluster. In their extended study [18] they formulated the problem statement as predicting images' popularity and reported that TDA outperforms conventional clustering algorithms such as k-means and hierarchical clustering.…”

Section: Related Workmentioning

confidence: 99%

Topological Signature of 19th Century Novelists: Persistent Homology in Text Mining

Gholizadeh¹,

Seyeditabari²,

Zadrozny³

2018

BDCC

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Topological Data Analysis (TDA) refers to a collection of methods that find the structure of shapes in data. Although recently, TDA methods have been used in many areas of data mining, it has not been widely applied to text mining tasks. In most text processing algorithms, the order in which different entities appear or co-appear is being lost. Assuming these lost orders are informative features of the data, TDA may play a significant role in the resulted gap on text processing state of the art. Once provided, the topology of different entities through a textual document may reveal some additive information regarding the document that is not reflected in any other features from conventional text processing methods. In this paper, we introduce a novel approach that hires TDA in text processing in order to capture and use the topology of different same-type entities in textual documents. First, we will show how to extract some topological signatures in the text using persistent homology-i.e., a TDA tool that captures topological signature of data cloud. Then we will show how to utilize these signatures for text classification.

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“…Many practical complex networks, covering different fields such as communication networks and social networks [ 8 , 9 ], all undertake the objective of information transmission. Especially for communication networks, information is the most fundamental element.…”

Section: Introductionmentioning

confidence: 99%

A New Model for Complex Dynamical Networks Considering Random Data Loss

Jiang

Wang

2019

Entropy

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Model construction is a very fundamental and important issue in the field of complex dynamical networks. With the state-coupling complex dynamical network model proposed, many kinds of complex dynamical network models were introduced by considering various practical situations. In this paper, aiming at the data loss which may take place in the communication between any pair of directly connected nodes in a complex dynamical network, we propose a new discrete-time complex dynamical network model by constructing an auxiliary observer and choosing the observer states to compensate for the lost states in the coupling term. By employing Lyapunov stability theory and stochastic analysis, a sufficient condition is derived to guarantee the compensation values finally equal to the lost values, namely, the influence of data loss is finally eliminated in the proposed model. Moreover, we generalize the modeling method to output-coupling complex dynamical networks. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed model.

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Extracting Knowledge from the Geometric Shape of Social Network Data Using Topological Data Analysis

Cited by 13 publications

References 42 publications

Semantic Network Analysis of Legacy News Media Perception in South Korea: The Case of PyeongChang 2018

Semantic Network Analysis of Legacy News Media Perception in South Korea: The Case of PyeongChang 2018

Topological Signature of 19th Century Novelists: Persistent Homology in Text Mining

A New Model for Complex Dynamical Networks Considering Random Data Loss

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