Capturing Planned Protests from Open Source Indicators

AI Magazine ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 63-75
Author(s):  
Sathappan Muthiah ◽  
Bert Huang ◽  
Jaime Arredondo ◽  
David Mares ◽  
Lise Getoor ◽  
...  
Keyword(s):  
Social Media ◽  
News Media ◽  
Lead Time ◽  
Authoritarian Regimes ◽  
Future Time ◽  
Civil Unrest ◽  
Trade Offs ◽  
Soft Logic ◽  
Forecasting System ◽  
Average Lead

Civil unrest events (protests, strikes, and “occupy” events) are common occurrences in both democracies and authoritarian regimes. The study of civil unrest is a key topic for political scientists as it helps capture an important mechanism by which citizenry express themselves. In countries where civil unrest is lawful, qualitative analysis has revealed that more than 75 percent of the protests are planned, organized, or announced in advance; therefore detecting references to future planned events in relevant news and social media is a direct way to develop a protest forecasting system. We report on a system for doing that in this article. It uses a combination of keyphrase learning to identify what to look for, probabilistic soft logic to reason about location occurrences in extracted results, and time normalization to resolve future time mentions. We illustrate the application of our system to 10 countries in Latin America: Argentina, Brazil, Chile, Colombia, Ecuador, El Salvador, Mexico, Paraguay, Uruguay, and Venezuela. Results demonstrate our successes in capturing significant societal unrest in these countries with an average lead time of 4.08 days. We also study the selective superiorities of news media versus social media (Twitter, Facebook) to identify relevant trade-offs.

scholarly journals Potential application of hydrological ensemble prediction in forecasting floods and its components over the Yarlung Zangbo River basin, China

2019 ◽  
Vol 23 (8) ◽  
pp. 3335-3352 ◽  
Author(s):  
Li Liu ◽  
Yue Ping Xu ◽  
Su Li Pan ◽  
Zhi Xu Bai
Keyword(s):  
Lead Time ◽  
Flood Forecasting ◽  
Base Flow ◽  
Ensemble Prediction ◽  
The Tibetan Plateau ◽  
Infiltration Capacity ◽  
Trade Offs ◽  
Yarlung Zangbo River ◽  
Forecasting System ◽  
Flow Components

Abstract. In recent year, floods becomes a serious issue in the Tibetan Plateau (TP) due to climate change. Many studies have shown that ensemble flood forecasting based on numerical weather predictions can provide an early warning with extended lead time. However, the role of hydrological ensemble prediction in forecasting flood volume and its components over the Yarlung Zangbo River (YZR) basin, China, has not been investigated. This study adopts the variable infiltration capacity (VIC) model to forecast the annual maximum floods and annual first floods in the YZR based on precipitation and the maximum and minimum temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF). N simulations are proposed to account for parameter uncertainty in VIC. Results show that when trade-offs between multiple objectives are significant, N simulations are recommended for better simulation and forecasting. This is why better results are obtained for the Nugesha and Yangcun stations. Our ensemble flood forecasting system can skillfully predict the maximum floods with a lead time of more than 10 d and can predict about 7 d ahead for meltwater-related components. The accuracy of forecasts for the first floods is inferior, with a lead time of only 5 d. The base-flow components for the first floods are insensitive to lead time, except at the Nuxia station, whilst for the maximum floods an obvious deterioration in performance with lead time can be recognized. The meltwater-induced surface runoff is the most poorly captured component by the forecast system, and the well-predicted rainfall-related components are the major contributor to good performance. The performance in 7 d accumulated flood volumes is better than the peak flows.

scholarly journals Introduction to special issue about election reporting: Why journalism (still) matters

Journalism ◽  
2019 ◽  
Vol 20 (8) ◽  
pp. 985-993 ◽  
Author(s):  
Stephen Cushion ◽  
Daniel Jackson
Keyword(s):  
Social Media ◽  
Political Parties ◽  
Political Communication ◽  
News Media ◽  
Election Campaigns ◽  
Special Issue ◽  
Technological Advances ◽  
Campaign Coverage ◽  
Election Coverage ◽  
Social Media Platforms

This introduction unpacks the eight articles that make up this Journalism special issue about election reporting. Taken together, the articles ask: How has election reporting evolved over the last century across different media? Has the relationship between journalists and candidates changed in the digital age of campaigning? How do contemporary news values influence campaign coverage? Which voices – politicians, say or journalists – are most prominent? How far do citizens inform election coverage? How is public opinion articulated in the age of social media? Are sites such as Twitter developing new and distinctive election agendas? In what ways does social media interact with legacy media? How well have scholars researched and theorised election reporting cross-nationally? How can research agendas be enhanced? Overall, we argue this Special Issue demonstrates the continued strength of news media during election campaigns. This is in spite of social media platforms increasingly disrupting and recasting the agenda setting power of legacy media, not least by political parties and candidates who are relying more heavily on sites such as Facebook, Instagram and Twitter to campaign. But while debates in recent years have centred on the technological advances in political communication and the associated role of social media platforms during election campaigns (e.g. microtargeting voters, spreading disinformation/misinformation and allowing candidates to bypass media to campaign), our collection of studies signal the enduring influence professional journalists play in selecting and framing of news. Put more simply, how elections are reported still profoundly matters in spite of political parties’ and candidates’ more sophisticated use of digital campaigning.

Political Knowledge and Misinformation in the Era of Social Media: Evidence From the 2015 UK Election

2020 ◽  
pp. 1-21
Author(s):  
Kevin Munger ◽  
Patrick J. Egan ◽  
Jonathan Nagler ◽  
Jonathan Ronen ◽  
Joshua Tucker
Keyword(s):  
Social Media ◽  
Political Parties ◽  
News Media ◽  
Political Knowledge ◽  
Public Affairs ◽  
Political Information ◽  
The Political ◽  
Election Campaign ◽  
Social Media Platform ◽  
Media Platform

Abstract Does social media educate voters, or mislead them? This study measures changes in political knowledge among a panel of voters surveyed during the 2015 UK general election campaign while monitoring the political information to which they were exposed on the Twitter social media platform. The study's panel design permits identification of the effect of information exposure on changes in political knowledge. Twitter use led to higher levels of knowledge about politics and public affairs, as information from news media improved knowledge of politically relevant facts, and messages sent by political parties increased knowledge of party platforms. But in a troubling demonstration of campaigns' ability to manipulate knowledge, messages from the parties also shifted voters' assessments of the economy and immigration in directions favorable to the parties' platforms, leaving some voters with beliefs further from the truth at the end of the campaign than they were at its beginning.

scholarly journals Source Trust and COVID-19 Information Sharing: The Mediating Roles of Emotions and Beliefs About Sharing

2020 ◽  
pp. 109019812098476
Author(s):  
Linqi Lu ◽  
Jiawei Liu ◽  
Y. Connie Yuan ◽  
Kelli S. Burns ◽  
Enze Lu ◽  
...  
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Health Information ◽  
News Media ◽  
Health Professionals ◽  
Government Agencies ◽  
Specific Information ◽  
Academic Institutions ◽  
Source Trust ◽  
Health Information Sharing

Health information sharing has become especially important during the COVID-19 (coronavirus disease 2019) pandemic because people need to learn about the disease and then act accordingly. This study examines the perceived trust of different COVID-19 information sources (health professionals, academic institutions, government agencies, news media, social media, family, and friends) and sharing of COVID-19 information in China. Specifically, it investigates how beliefs about sharing and emotions mediate the effects of perceived source trust on source-specific information sharing intentions. Results suggest that health professionals, academic institutions, and government agencies are trusted sources of information and that people share information from these sources because they think doing so will increase disease awareness and promote disease prevention. People may also choose to share COVID-19 information from news media, social media, and family as they cope with anxiety, anger, and fear. Taken together, a better understanding of the distinct psychological mechanisms underlying health information sharing from different sources can help contribute to more effective sharing of information about COVID-19 prevention and to manage negative emotion contagion during the pandemic.

scholarly journals A Multi-platform Approach to Monitoring Negative Dominance for COVID-19 Vaccine-Related Information Online

2021 ◽  
pp. 1-24
Author(s):  
Paola Pascual-Ferrá ◽  
Neil Alperstein ◽  
Daniel J. Barnett
Keyword(s):  
Social Media ◽  
Adverse Events ◽  
News Media ◽  
Search Behavior ◽  
Social Media Data ◽  
Future Studies ◽  
Related Information ◽  
Youtube Videos ◽  
Negative Dominance ◽  
Media Data

Abstract Objective The aim of this study was to test the appearance of negative dominance in COVID-19 vaccine-related information and activity online. We hypothesized that if negative dominance appeared, it would be a reflection of peaks in adverse events related to the vaccine, that negative content would attract more engagement on social media than other vaccine-related posts, and posts referencing adverse events related to COVID-19 vaccination would have a higher average toxicity score. Methods We collected data using Google Trends for search behavior, CrowdTangle for social media data, and Media Cloud for media stories, and compared them against the dates of key adverse events related to COVID-19. We used Communalytic to analyze the toxicity of social media posts by platform and topic. Results While our first hypothesis was partially supported, with peaks in search behavior for image and YouTube videos driven by adverse events, we did not find negative dominance in other types of searches or patterns of attention by news media or on social media. Conclusion We did not find evidence in our data to prove the negative dominance of adverse events related to COVID-19 vaccination on social media. Future studies should corroborate these findings and, if consistent, focus on explaining why this may be the case.

New Indian online rules risk state overreach and abuse

2021 ◽  
Keyword(s):  
Social Media ◽  
News Media ◽  
Public Discourse ◽  
Hate Speech ◽  
Central Government ◽  
Service Providers ◽  
Online News ◽  
Content Type ◽  
Digital Service ◽  
The Government

Significance The new rules follow a stand-off between Twitter and the central government last month over some posts and accounts. The government has used this stand-off as an opportunity not only to tighten rules governing social media, including Twitter, WhatsApp, Facebook and LinkedIn, but also those for other digital service providers including news publishers and entertainment streaming companies. Impacts Government moves against dominant social media platforms will boost the appeal of smaller platforms with light or no content moderation. Hate speech and harmful disinformation are especially hard to control and curb on smaller platforms. The new rules will have a chilling effect on online public discourse, increasing self-censorship (at the very least). Government action against online news media would undercut fundamental democratic freedoms and the right to dissent. Since US-based companies dominate key segments of the Indian digital market, India’s restrictive rules could mar India-US ties.

scholarly journals Advancing children’s news media literacy: learning from the practices and experiences of young Australians

2018 ◽  
Vol 41 (5) ◽  
pp. 689-707
Author(s):  
Tanya Notley ◽  
Michael Dezuanni
Keyword(s):  
Social Media ◽  
Media Literacy ◽  
News Media ◽  
Social Impact ◽  
Literacy Learning ◽  
Literacy Education ◽  
Fake News ◽  
News Stories ◽  
Media Literacy Education ◽  
Nationally Representative

Social media use has redefined the production, experience and consumption of news media. These changes have made verifying and trusting news content more complicated and this has led to a number of recent flashpoints for claims and counter-claims of ‘fake news’ at critical moments during elections, natural disasters and acts of terrorism. Concerns regarding the actual and potential social impact of fake news led us to carry out the first nationally representative survey of young Australians’ news practices and experiences. Our analysis finds that while social media is one of young people’s preferred sources of news, they are not confident about spotting fake news online and many rarely or never check the source of news stories. Our findings raise important questions regarding the need for news media literacy education – both in schools and in the home. Therefore, we consider the historical development of news media literacy education and critique the relevance of dominant frameworks and pedagogies currently in use. We find that news media has become neglected in media literacy education in Australia over the past three decades, and we propose that current media literacy frameworks and pedagogies in use need to be rethought for the digital age.

scholarly journals Seasonal forecasts of droughts in African basins using the Standardized Precipitation Index

2013 ◽  
Vol 17 (6) ◽  
pp. 2359-2373 ◽  
Author(s):  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Wetterhall ◽  
F. Pappenberger
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Seasonal Forecasting ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Forecasting System ◽  
The Standardized Precipitation Index

Abstract. Vast parts of Africa rely on the rainy season for livestock and agriculture. Droughts can have a severe impact in these areas, which often have a very low resilience and limited capabilities to mitigate drought impacts. This paper assesses the predictive capabilities of an integrated drought monitoring and seasonal forecasting system (up to 5 months lead time) based on the Standardized Precipitation Index (SPI). The system is constructed by extending near-real-time monthly precipitation fields (ECMWF ERA-Interim reanalysis and the Climate Anomaly Monitoring System–Outgoing Longwave Radiation Precipitation Index, CAMS-OPI) with monthly forecasted fields as provided by the ECMWF seasonal forecasting system. The forecasts were then evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi. There are significant differences in the quality of the precipitation between the datasets depending on the catchments, and a general statement regarding the best product is difficult to make. The generally low number of rain gauges and their decrease in the recent years limits the verification and monitoring of droughts in the different basins, reinforcing the need for a strong investment on climate monitoring. All the datasets show similar spatial and temporal patterns in southern and north-western Africa, while there is a low correlation in the equatorial area, which makes it difficult to define ground truth and choose an adequate product for monitoring. The seasonal forecasts have a higher reliability and skill in the Blue Nile, Limpopo and Upper Niger in comparison with the Zambezi. This skill and reliability depend strongly on the SPI timescale, and longer timescales have more skill. The ECMWF seasonal forecasts have predictive skill which is higher than using climatology for most regions. In regions where no reliable near-real-time data is available, the seasonal forecast can be used for monitoring (first month of forecast). Furthermore, poor-quality precipitation monitoring products can reduce the potential skill of SPI seasonal forecasts in 2 to 4 months lead time.

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