Measuring The Influence In The News Media’s Narratives

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Presentation transcript:

Measuring The Influence In The News Media’s Narratives Yuchong Zheng

CONTENTS 01 02 03 04 Introduction Related Work Methodology Design and Result

01 PART Introduction

The Importance of Measuring Data Function Important Parts Research in the fields of psychology and neuroscience has play a higher role in some processes such as judgment and decision making. So the collect of Data can play an important role in research. There are mainly two important parts of studying the conviction narratives. First, it can be a significant part of knowing the opinion of the citizens. Second, it is also a warning signal for identifying the unexpected message. Key Point Purpose The research focuses on a societal level about how to identify the conviction narratives and how to recognize the data, when it is a dominate in the society(Measuring a data and test its influence at a social level) This paper tests the hypothesis that it is very possible to automatically identify conviction narratives as they emerge in text data and measure how actors interact through conviction narratives by identify the influence.

A Brief Introduction of CNT What is CNT The Radical Uncertainty Conviction Narrative Theory(CNT) is a social psychological theory of affective cognition. It aims to deal with the radical uncertainty problem. This is a decision which includes complex judgments. They are a few typical examples from the inbox of challenges requiring decisions society that is more rapidly interconnected and inter-dependent than ever before. Here we focus about how the humans are able to conjure up the conviction to make decision. Argument The Source of Data By framing a decision outcome as a narrative, CNT argues that agents can combine cognitive and emotional elements to interpolate missing pieces of Information and assess the plausibility of an outcome by determine whether the narrative has a coherent temporal and causal structure For the accurate and the achievement of actual effect analysis, this paper use a corpus of historical online news articles from the period May 2016 to December 2016 and show that there are statistically significant lead-lag relationships in the online news media

02 PART Related Work

There are indeed a few papers discuss about the topic Conviction Narrative Theory and the conclusion are shown as below. 1. When the object of a conviction narrative is known a priori or the changes in the narratives, then it can be detected and tracked in the data. 2. Conviction narratives can disseminate through social networks and that the net work can become “fixated” on the narratives. And there is a lack of diversity of opinions.

Intermedia agenda setting Weakness of These Papers Similar Works 01 Intermedia agenda setting Verga and Guo examine online U.S media and show that the agendas set by the media are both homogenous and reciprocal, and agenda-setting across media sources is generated from partisan sources. 02 Other Researches Another scientist Meraz identifies the influence in media networks as well as convergence behavior in the topics being discussed across source. 03 Weakness of These Papers Both studies only concerned about the topic discussed in the news, and not the way it was being discussed. In this paper the author is concerned specifically with whether the topic evokes approach or avoidance emotions.

The Focus on the Research Research focusing on intersection between sentiment and social network influence has primarily been looked at micro blogging websites such as Twitter and Facebook. 1.Sources 2.Models The inclusion of semantic information, specially sentiment and opinions, expressed by actors in social media has been proposed as a method to augment influencer detection beyond what is possible using only network topology. Contagion models have been developed to study how emotion and emotive content propagates and diffused throughout social networks.

03 PART Methodology

What is conviction narrative Definition and Argument Argument In this paper the authors argue that it is possible to identify the impact of conviction narratives with two features: The object of the narrative. The emotion that the narrative evokes. What is conviction narrative A conviction narrative is the subjective and imagined unfolding of an event sequence and the emotion that event evokes in the mind of the person conjuring the narrative.

Method and Setting With the argument which mentioned above, the author sets a series of assignment to analyze the project as a topic-sentiment pair. The topic of the narrative are assumed to be constant over time and the sentiment expressed about those topics may change over time and is measured for each agent separately. And the topic-sentiment assignment are showed as below. The topic-specific sentiment for each source is measured daily. This is done by inferring the sentiment of each news article and using an LDA model to assign the article a topic distribution. To determine how a particular news source feels about a particular topic on any given day, the topic probabilities for each other of its articles are scaled by their sentiment, and then summed together across articles.

The analysis of the Method The sentiment of each article is determined using a set of “excitement” and “anxiety” sentiment keyword constructed by psychoanalysis experts and designed to identify approach and avoidance emotions of conviction narratives. The sentiment of an article is found by taking the difference between the number of excitement keywords and the number of anxiety keywords. And then these keywords are normalizing by the total number of the tokens in the article. When keywords approach to analyzing sentiment, they nonetheless offer several advantages compared to statistical compared methods because machine learning methods are more expensive and statistical methods are not guaranteed to generalize to news tests when dealing shorter tests.

04 PART Design and Result

1 2 Dataset 3 4 Dataset and Preprocessing The source of the news articles which used in the research is the LexisNexis News-desk dataset. 1 Dataset 2 Dataset consists of 113,000,000 articles form over 34,000 news sources from 6 May 2016 to 31 December 2016. The sources of data are combined with different sources such as Sport, Fashion and so on. And the article between 100 to 700 words are kept. 3 4 Also, all sources with an average publication rate lower than once per day are ignored. It leaves only 92 news sources.

Experiment Results The first test aims to look at the actor which leads the narratives of the rest of the online media. Here we take LDA topics and test if there are new sources sentiment on particular topic and lead the indicator for the “consensus view” being put forth by the other sources on that topic. The presence of a lead-lag relationship between a particular source is tested by performing a Granger causality test. The result shows that for a random subset of online news sources, the percentage of topics that the sources have been found to be opinions leaders on with a p-value 0.01 or less.

Experiment Results After finding the influencers online media, the article keeps on finding if the sources have influence on each others or whether the effect of influencers is only at the aggregate level. For each topics the article takes all pairs of news sources and test if the sentiment of one source have a leader relationship than others. In other words, it takes all pairs of news sources and test whether the sentiment of one source is a leading indicator of the sentiment of the other

Experimental Results 1. There are statistically significant lead-lag relationships, which shows that the narratives of some news are dictated by others. 2. The influence does not appear to be contained to a small minority of sources, but rather that most sources influence the narratives of multiple other sources. 3. The majority of the sources influence multiple other sources, which indicate that there are connection of webs and web sources.

THANKS