scholarly journals Intermedia Agenda Setting in the Social Media Age: How Traditional Players Dominate the News Agenda in Election Times

2017 ◽  
Vol 22 (3) ◽  
pp. 275-293 ◽  
Author(s):  
Raymond A. Harder ◽  
Julie Sevenans ◽  
Peter Van Aelst
Keyword(s):  
Social Media ◽  
News Media ◽  
Agenda Setting ◽  
Time Series Data ◽  
Fixed Time ◽  
Series Data ◽  
News Story ◽  
Time Lags ◽  
Intermedia Agenda Setting ◽  
Twitter Users

Intermedia agenda setting is a widely used theory to explain how content transfers between news media. The recent digitalization wave, however, challenges some of its basic presuppositions. We discuss three assumptions that cannot be applied to online and social media unconditionally: one, that media agendas should be measured on an issue level; two, that fixed time lags suffice to understand overlap in media content; and three, that media can be considered homogeneous entities. To address these challenges, we propose a “news story” approach as an alternative way of mapping how news spreads through the media. We compare this with a “traditional” analysis of time-series data. In addition, we differentiate between three groups of actors that use Twitter. For these purposes, we study online and offline media alike, applying both measurement methods to the 2014 Belgium election campaign. Overall, we find that online media outlets strongly affect other media that publish less often. Yet, our news story analysis emphasizes the need to look beyond publication schemes. “Slow” newspapers, for example, often precede other media’s coverage. Underlining the necessity to distinguish between Twitter users, we find that media actors on Twitter have vastly more agenda-setting influence than other actors do.

When politics intervenein non-political news flow

2020 ◽  
Vol 4 (2) ◽  
pp. 173-194
Author(s):  
Yiyan Zhang
Keyword(s):  
News Media ◽  
Agenda Setting ◽  
Time Series Data ◽  
News Coverage ◽  
Mainland China ◽  
Real Life ◽  
Online News ◽  
Global Perspective ◽  
Series Data ◽  
Intermedia Agenda Setting

Abstract While intermedia agenda-setting scholars have examined the process from a global perspective, trans-regional intermedia agenda setting, especially in non-western context, remains understudied. By analyzing the time-series data of news coverage on air pollution, a non-political topic, from online news media in mainland China, Hong Kong, and Taiwan from 2015 to 2018, this study revealed a triangular first-level agenda-setting relationship among the three regions and identified the changing agenda setters across years, which disproves the imperialistic stereotype that there is a one-way control from mainland China media. The study also revealed the significant yet unconventional moderating effect of the political stance of news organizations in the trans-regional information flow. This study contributes to the intermedia agenda-setting literature by introducing the method of controlling the real-life situation in the Granger Causality test and by showing that non-political issues can also be politicalized in the salience transferring process.

scholarly journals News values on social media: Exploring what drives peaks in user activity about organizations on Twitter

Journalism ◽  
2018 ◽  
Vol 21 (5) ◽  
pp. 633-651 ◽  
Author(s):  
Theo Araujo ◽  
Toni GLA van der Meer
Keyword(s):  
Social Media ◽  
News Media ◽  
Social Impact ◽  
News Coverage ◽  
Value Theory ◽  
News Values ◽  
News Value ◽  
Twitter Users ◽  
Nuanced Understanding ◽  
Twitter Activity

Since news circulation increasingly takes place online, the public has gained the capacity to influence the salience of topics on the agenda, especially when it comes to social media. Considering increased scrutiny about organizations, this study aims to understand what causes heightened activity to organization-related topics among Twitter users. We explore the extent to which news value theory, news coverage, and influential actors can explain peaks in Twitter activity about organizations. Based on a dataset of 1.8 million tweets about 18 organizations, the findings show that the news values social impact, geographical closeness, facticity, as well as certain influential actors, can explain the intensity of online activities. Moreover, the results advocate for a more nuanced understanding of the relation between news media and social media users, as indications of reversed agenda-setting patterns were observed.

scholarly journals Analysing inter-media agenda setting influence between Social media and electronic media; a perspective from Pakistan

2020 ◽  
Vol Volume 4 (Issue 2) ◽  
pp. 478-496
Author(s):  
Farrukh Shahzad ◽  
Prof. Dr. Syed Abdul Siraj
Keyword(s):  
Social Media ◽  
News Media ◽  
Agenda Setting ◽  
News Coverage ◽  
Electronic Media ◽  
Analysis Method ◽  
Traditional Media ◽  
Media Agenda ◽  
Content Analysis Method ◽  
Lagged Correlation

Inter-media agenda setting is a commonly used phenomenon to investigate the transfer of contents between news media. The recent digitization era challenges the traditional presuppositions. This study investigates the inter-media agenda setting influence between social media and traditional media. To address this question, the present study investigates first level agenda setting between Twitter and ARY news during Farishta murder case 2019. Content analysis method was used to assess agendas present within Twitter and ARY news. By employing cross-lagged correlation, the study investigates the inter-media agenda setting influence between Twitter agendas and of ARY news agendas. Aggregate findings of cross-lagged correlation reveal a clear agenda setting influence of Twitter on ARY news coverage agenda about Farishta murder case. The results of the study suggest that Twitter has the capability to influence broadcast agendas of television in Pakistan

scholarly journals Partial Correlation-Based Attention for Multivariate Time Series Forecasting

2020 ◽  
Vol 34 (10) ◽  
pp. 13720-13721
Author(s):  
Won Kyung Lee
Keyword(s):  
Time Series ◽  
Partial Correlation ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Time Series Forecasting ◽  
Data Driven ◽  
Series Data ◽  
Time Lags ◽  
Dependency Structure ◽  
Agnostic Learning

A multivariate time-series forecasting has great potentials in various domains. However, it is challenging to find dependency structure among the time-series variables and appropriate time-lags for each variable, which change dynamically over time. In this study, I suggest partial correlation-based attention mechanism which overcomes the shortcomings of existing pair-wise comparisons-based attention mechanisms. Moreover, I propose data-driven series-wise multi-resolution convolutional layers to represent the input time-series data for domain agnostic learning.

scholarly journals The Impact of Web Site Campaigning on Traditional News Media and Public Information Processing

2003 ◽  
Vol 80 (3) ◽  
pp. 528-547 ◽  
Author(s):  
Gyotae Ku ◽  
Lynda Lee Kaid ◽  
Michael Pfau
Keyword(s):  
News Media ◽  
Agenda Setting ◽  
Web Site ◽  
Public Information ◽  
Election Campaign ◽  
The Public ◽  
Intermedia Agenda Setting ◽  
Setting Approach ◽  
The Impact ◽  
Flow Of Information

This study examined the impact of Web site campaigning on traditional news media agendas and on public opinion during the 2000presidential election campaign. Based on an intermedia agenda-setting approach, this study demonstrated the direction of influence among three media in terms of the flow of information. An agenda-setting impact of Web site campaigning on the public was also identified.

scholarly journals Prediction of the Infectious Outbreak COVID-19 and Prevalence of Anxiety: Global Evidence

2021 ◽  
Vol 13 (20) ◽  
pp. 11339
Author(s):  
Daniyal Alghazzawi ◽  
Atika Qazi ◽  
Javaria Qazi ◽  
Khulla Naseer ◽  
Muhammad Zeeshan ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Disease Outbreaks ◽  
Epidemiological Data ◽  
World Health ◽  
Series Data ◽  
Systems Science ◽  
Support Vector ◽  
Twitter Users ◽  
Health Organization

Forecasting disease outbreaks in real-time using time-series data can help for the planning of public health interventions. We used a support vector machine (SVM) model using epidemiological data provided by Johns Hopkins University Centre for Systems Science and Engineering (JHU CCSE), World Health Organization (WHO), and the Centers for Disease Control and Prevention (CDC) to predict upcoming records before the WHO made an official declaration. Our study, conducted on the time series data available from 22 January till 10 March 2020, revealed that COVID-19 was spreading at an alarming rate and progressing towards a pandemic. The initial insight that confirmed COVID-19 cases were increasing was because these received the highest number of effects for our selected dataset from 22 January to 10 March 2020, i.e., 126,344 (64%). The recovered cases were 68289 (34%), and the death rate was around 2%. Moreover, we classified the tweets from 22 January to 15 April 2020 into positive and negative sentiments to identify the emotions (stress or relaxed) posted by Twitter users related to the COVID-19 pandemic. Our analysis identified that tweets mostly conveyed a negative sentiment with a high frequency of words for #coronavirus and #lockdown amid COVID-19. However, these anxiety tweets are an alarm for healthcare authorities to devise plans accordingly.

scholarly journals Tweets, tents, and events: The interplay between street protests and social media

2017 ◽  
Author(s):  
Marco T. Bastos ◽  
Dan Mercea ◽  
Arthur Charpentier
Keyword(s):  
Social Media ◽  
Time Series ◽  
Granger Causality ◽  
Time Series Data ◽  
Series Data ◽  
Political Unrest ◽  
Protest Activity

Recent protests have fuelled deliberations about the extent to which social media ignites popular uprisings. In this paper we use time-series data of Twitter, Facebook, and onsite protests to assess the Granger-causality between social media streams and onsite developments at the Indignados, Occupy, and Brazilian Vinegar protests. After applying a Gaussianization procedure to the data, we found that contentious communication on Twitter and Facebook forecasted onsite protest during the Indignados and Occupy protests, with bidirectional Granger-causality between online and onsite protest in the Occupy series. Conversely, the Vinegar demonstrations presented Granger-causality between Facebook and Twitter communication, and separately between protestors and injuries/arrests onsite. We conclude that the effective forecasting of protest activity likely varies across different instances of political unrest.

scholarly journals Intermedia agenda setting in personalized campaigns: How news media influence the importance of leaders

2018 ◽  
Vol 54 ◽  
pp. 281-288 ◽  
Author(s):  
Susan Banducci ◽  
Iulia Cioroianu ◽  
Travis Coan ◽  
Gabriel Katz ◽  
Daniel Stevens
Keyword(s):  
News Media ◽  
Agenda Setting ◽  
Media Influence ◽  
Intermedia Agenda Setting

scholarly journals The Emergence of the Philippine "Anti-Media": The Duterte Factor

2017 ◽  
Vol 14 (1) ◽  
pp. 61
Author(s):  
Jermaine Vistro Beltran
Keyword(s):  
Qualitative Research ◽  
Social Media ◽  
News Media ◽  
Agenda Setting ◽  
Research Method ◽  
Virtual Community ◽  
The Internet ◽  
Qualitative Research Method ◽  
Setting Theory

The Philippine news media is perceived to be the freest in Asia. However, it also has its faults which its audiences have noticed. This study was aimed at exploring the factors which have lead to the audience’s dissent and subsequent emergence of an online anti-media movement. A qualitative research method was utilized where in social media posts and websites were analyzed with the Agenda Setting Theory to explain the frames being made by the mainstream and anti-media. The results showed factors such as the internet and its tools in creating a new virtual community.

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