Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation

Luo, Xiangfeng; Xuan, Junyu; Lu, Jie; Zhang, Guangquan

doi:10.1145/2903719

Cited by 7 publications

(4 citation statements)

References 53 publications

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“…Some complications are raised in extracting information, such as language ambiguity (TROVATI et al, 2017), (SONG; KIM; KIM, 2015)(LI; SUN; DATTA, 2013) and information redundancy (WANG et al, 2011)(GAMBHIR;GUPTA, 2016). Scientific writing is different from everyday writing, it employs structures and semantics designed to formulate and organize knowledge (LUO et al, 2016), such as making a hypothesis, analyzing data and drawing scientific conclusions (MOOHEBAT et al, 2014).…”

Section: Information Extractionmentioning

confidence: 99%

Knowledge Extraction From Scientific Articles: A Proposal for Initial Research Methodology on Text Mining

Ancioto¹,

Dantas²

2022

JER

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The need to extract textual information encourages the development of automated tools for document reading, pattern recognition and knowledge extraction. The large amount of scientific content available on the internet makes it difficult to search for the most relevant and up-to-date information. In this work, a research methodology is performed to support the process of information retrieval in a scientific environment with the initial theme of Text Mining. Steps were defined for searching, visualizing and filtering data, through computational tools, with the objective of finding relevant scientific material with assertiveness. The method resulted in a list of 49 published articles with an average impact factor of 2.193, material that was compiled and used for initial mapping of the topic. It is concluded that the initial research methodology proposal provides results with a reduced time, with relevance to the material and that the use of general-purpose computational tools, even with a lot of manual intervention, helps to define the initial state of a scientific research. Text mining can make the extraction of knowledge from scientific research already produced more productive, promoting the identification of the state of the art and research gaps.

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Section: Information Extractionmentioning

confidence: 99%

Knowledge Extraction From Scientific Articles: A Proposal for Initial Research Methodology on Text Mining

Ancioto¹,

Dantas²

2022

JER

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“…Radinsky et al [28] described a system that uses causality extraction to obtain pairs of terms that have a causal relation and that are later used to train a prediction algorithm. Luo et al [22] also address this problem by introducing the concept of semantic uncertainty, which is used to estimate the most certain next state based on the current state, or event. is approach is particularly useful when there is limited historical data available.…”

Section: Related Workmentioning

confidence: 99%

Analyzing evolving stories in news articles

Barranco

Boedihardjo

Hossain

2017

Int J Data Sci Anal

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ere is an overwhelming number of news articles published every day around the globe. Following the evolution of a news-story is a di cult task given that there is no such mechanism available to track back in time to study the di usion of the relevant events in digital news feeds. e techniques developed so far to extract meaningful information from a massive corpus rely on similarity search, which results in a myopic loopback to the same topic without providing the needed insights to hypothesize the origin of a story that may be completely di erent than the news today. In this paper, we present an algorithm that mines historical data to detect the origin of an event, segments the timeline into disjoint groups of coherent news articles, and outlines the most important documents in a timeline with a so probability to provide a be er understanding of the evolution of a story.alitative and quantitative approaches to evaluate our framework demonstrate that our algorithm discovers statistically signi cant and meaningful stories in reasonable time. Additionally, a relevant case study on a set of news articles demonstrates that the generated output of the algorithm holds the promise to aid prediction of future entities in a story.

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“…The news media has a considerable ability to examine public concerns and respond to national public policies. Luo, et al [6] indicated that if a news event with a large potential for evolution is known in advance, then its resultant public relations crisis or response can be dealt with in sufficient time. Therefore, news events can help in making government policy decisions and responding to public concerns with news events.…”

Section: Introductionmentioning

confidence: 99%

Adapting the influences of publishers to perform news event detection

Chen

Wang

2021

Journal of Information Science

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Online news outlets have the power to influence public policy issues. To understand the opinions of the people, many government departments check online news outlets to manually detect events that interest people. This process is time-consuming. To promptly respond to public expectations, this research proposes a framework for detecting news events that may interest government departments. This article proposes a method for finding event trigger words used to represent an event. The news media can be a critical participant in ‘agenda-setting’, which means that more widely discussed news is more attractive and critical than news that is less discussed. However, few studies have considered the influence of news media publishers from the ‘agenda setting’ perspective. Therefore, this study proposes an ‘agenda setting’-based filter to establish a high-impact news event detection model. The proposed framework identifies trigger words and utilises word embedding to find news event–related words. After that, an event detection model is designed to determine the events that are attractive to government departments. The experimental results show that purity increases from 0.666 when no extraction method is used to 0.809 when the extraction method in this study is used. The overall improvement trend shows significant improvement in event detection performance.

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Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation

Cited by 7 publications

References 53 publications

Knowledge Extraction From Scientific Articles: A Proposal for Initial Research Methodology on Text Mining

Knowledge Extraction From Scientific Articles: A Proposal for Initial Research Methodology on Text Mining

Analyzing evolving stories in news articles

Adapting the influences of publishers to perform news event detection

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