scholarly journals The climate change movement and political parties: Mechanisms of social media and interaction during the 2019 electoral period in Finland

2021 ◽  
Vol 3 (1) ◽  
pp. 40-60
Author(s):  
Sonja Savolainen ◽  
Tuomas Ylä-Anttila
Keyword(s):  
Climate Change ◽  
Social Media ◽  
Social Movements ◽  
Political Parties ◽  
Comparative Studies ◽  
Social Media Data ◽  
Interaction Dynamics ◽  
The Government ◽  
Media Data

Abstract Building on the framework of electoral contention, we investigate the interaction dynamics between social movements and political parties during elections. We argue that social media today is an important venue for these interactions, and consequently, analysing social media data is useful for understanding the shifts in the conflict and alliance structures between movements and parties. We find that Twitter discussions on the climate change movement during the 2019 electoral period in Finland reveal a process of pre-election approaching and post-election distancing between the movement and parties. The Greens and the Left formed mutually beneficial coalitions with the movement preceding the elections and took distance from one another after these parties entered the government. These findings suggest that research on movement-party interaction should pay more attention to social media and undertake comparative studies to assess whether the approaching-distancing process and its constituent mechanisms characterise movements beyond the climate strikes in Finland.

scholarly journals Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social Media Data

10.2196/18796 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e18796 ◽  
Author(s):  
Qiuyan Liao ◽  
Jiehu Yuan ◽  
Meihong Dong ◽  
Lin Yang ◽  
Richard Fielding ◽  
...  
Keyword(s):  
Social Media ◽  
Public Engagement ◽  
Latent Class ◽  
Early Stage ◽  
Government Agency ◽  
Instrumental Support ◽  
Social Media Data ◽  
The Government ◽  
Government Responsiveness ◽  
Media Data

Background Effective risk communication about the outbreak of a newly emerging infectious disease in the early stage is critical for managing public anxiety and promoting behavioral compliance. China has experienced the unprecedented epidemic of the coronavirus disease (COVID-19) in an era when social media has fundamentally transformed information production and consumption patterns. Objective This study examined public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage based on an analysis of data from Sina Weibo, a major social media platform in China. Methods Weibo data relevant to COVID-19 from December 1, 2019, to January 31, 2020, were retrieved. Engagement data (likes, comments, shares, and followers) of posts from government agency accounts were extracted to evaluate public engagement with government posts online. Content analyses were conducted for a random subset of 644 posts from personal accounts of individuals, and 273 posts from 10 relatively more active government agency accounts and the National Health Commission of China to identify major thematic contents in online discussions. Latent class analysis further explored main content patterns, and chi-square for trend examined how proportions of main content patterns changed by time within the study time frame. Results The public response to COVID-19 seemed to follow the spread of the disease and government actions but was earlier for Weibo than the government. Online users generally had low engagement with posts relevant to COVID-19 from government agency accounts. The common content patterns identified in personal and government posts included sharing epidemic situations; general knowledge of the new disease; and policies, guidelines, and official actions. However, personal posts were more likely to show empathy to affected people (χ21=13.3, P<.001), attribute blame to other individuals or government (χ21=28.9, P<.001), and express worry about the epidemic (χ21=32.1, P<.001), while government posts were more likely to share instrumental support (χ21=32.5, P<.001) and praise people or organizations (χ21=8.7, P=.003). As the epidemic evolved, sharing situation updates (for trend, χ21=19.7, P<.001) and policies, guidelines, and official actions (for trend, χ21=15.3, P<.001) became less frequent in personal posts but remained stable or increased significantly in government posts. Moreover, as the epidemic evolved, showing empathy and attributing blame (for trend, χ21=25.3, P<.001) became more frequent in personal posts, corresponding to a slight increase in sharing instrumental support, praising, and empathizing in government posts (for trend, χ21=9.0, P=.003). Conclusions The government should closely monitor social media data to improve the timing of communications about an epidemic. As the epidemic evolves, merely sharing situation updates and policies may be insufficient to capture public interest in the messages. The government may adopt a more empathic communication style as more people are affected by the disease to address public concerns.

Using Social Media Data to Analyse Issue Engagement During the 2017 German Federal Election

2022 ◽  
Vol 22 (1) ◽  
pp. 1-25
Author(s):  
Florian Meier ◽  
Alexander Bazo ◽  
David Elsweiler
Keyword(s):  
Social Media ◽  
Political Parties ◽  
Political Science ◽  
Computational Social Science ◽  
The Political ◽  
Political Strategy ◽  
Political Debate ◽  
Social Media Data ◽  
Political Left ◽  
Media Data

A fundamental tenet of democracy is that political parties present policy alternatives, such that the public can participate in the decision-making process. Parties, however, strategically control public discussion by emphasising topics that they believe will highlight their strengths in voters’ minds. Political strategy has been studied for decades, mostly by manually annotating and analysing party statements, press coverage, or TV ads. Here we build on recent work in the areas of computational social science and eDemocracy, which studied these concepts computationally with social media. We operationalize issue engagement and related political science theories to measure and quantify politicians’ communication behavior using more than 366k Tweets posted by over 1,000 prominent German politicians in the 2017 election year. To this end, we first identify issues in posted Tweets by utilising a hashtag-based approach well known in the literature. This method allows several prominent issues featuring in the political debate on Twitter that year to be identified. We show that different political parties engage to a larger or lesser extent with these issues. The findings reveal differing social media strategies by parties located at different sides of the political left-right scale, in terms of which issues they engage with, how confrontational they are and how their strategies evolve in the lead-up to the election. Whereas previous work has analysed the general public’s use of Twitter or politicians’ communication in terms of cross-party polarisation, this is the first study of political science theories, relating to issue engagement, using politicians’ social media data.

Variations in the Temporal Structure of Sociability across American Cities

Sociology ◽  
2020 ◽  
pp. 003803852095694
Author(s):  
Dhiraj Murthy ◽  
John D O’Brien ◽  
Alexander Gross ◽  
Nathan Meyers
Keyword(s):  
Social Media ◽  
Social Movements ◽  
Temporal Structure ◽  
Geographic Proximity ◽  
Social Media Data ◽  
Highly Educated ◽  
Per Capita ◽  
Urban Contexts ◽  
American Cities ◽  
Media Data

Though sociologists have been interested in how temporal patterns of sociability vary in urban contexts, the study of city-level dynamics at short timescales has been challenging historically. Social media and new computational methods provide a solution. Our study clusters cities using sociality as a metric. We collected three months of social media data to investigate variation in the temporal structure of sociability across American cities. We find that cities cluster into three distinct types (‘Coastal’, ‘Transitional’ and ‘Heartland’) and that geographic proximity together with race, education and language associate with this clustering. Specifically, we found that clusters of Blacker cities tend to tweet more per capita, but also that more highly educated cities tend to tweet less per capita. These findings provide evidence that social media may be facilitating new opportunities to empower traditionally marginalized urban groups, a conclusion relevant to #BlackLivesMatter, the George Floyd protests and other social movements.

scholarly journals Temporal Characteristics of Waterfronts in Wuhan City and People’s Behavioral Preferences Based on Social Media Data

2019 ◽  
Vol 11 (22) ◽  
pp. 6308
Author(s):  
Jing Wu ◽  
Xirui Chen ◽  
Shulin Chen
Keyword(s):  
Social Media ◽  
Sustainable Urban Development ◽  
Social Media Data ◽  
Temporal Characteristics ◽  
Space Design ◽  
The Social ◽  
Behavioral Preferences ◽  
Cultural Themes ◽  
The Government ◽  
Media Data

The appeal and vibrancy of urban waterfronts are catalysts for urban progress and sustainable urban development. This study aims to thoroughly explore the temporal characteristics of waterfront vibrancy and explore people’s behavioral preferences for various types of waterfronts at various times. On the basis of social media data, this study uses the seasonal index analysis method to classify waterfronts. Then, the kernel density estimation was used to analyze the spatial structure of different types of waterfronts. Finally, temporally weighted regression was used to indicate people’s preferences for various types of waterfronts. In general, results show the different temporal characteristics of users in waterfronts at different times and their behavioral preferences for waterfronts as the reasons behind these preface characteristics. First, on weekdays, people tend to visit daily waterfronts close to residences, and people find it convenient to walk after 18:00 and engage in recreational activities dominated by consumption and exercise, which reach a peak at 22:00–24:00. Second, on weekends, people prefer the weekend waterfronts with complete entertainment facilities and cultural themes. The natural seasonal waterfronts with seasonal landscapes attract people in various seasons, such as spring and autumn, whereas the social seasonal waterfront may be more attractive during high seasons, especially in March and June, due to big water events or nearby colleges and universities. Therefore, the government should improve the facilities of various types of waterfronts to satisfy people’s preferences at different times and help in proposing targeted suggestions with reference to future city waterfront planning and space design, contributing to the waterfronts’ vitality improvement, urban features, and promotion of urban sustainable development.

scholarly journals Fake News Case Study during the Australian 2019 General Election

2020 ◽  
Vol 24 ◽  
Author(s):  
Matthew Warren
Keyword(s):  
Social Media ◽  
Political Parties ◽  
Ethical Issues ◽  
General Election ◽  
Fake News ◽  
Social Media Data ◽  
Research Perspective ◽  
Research Findings ◽  
Media Data

Social media is used by all aspects of society from citizens to businesses, but it also now used by political parties. Political parties use social media to engage with voters as a method of attract new voters or reinforcing the views of political parties’ current supporters. An important consideration is the ethical conduct of political parties and politicians in how they use social media. It is now recognized that social media can also have negative aspects seen by the introduction of Fake News. These negative aspects of social media are often overlooked and have not been explored from a research perspective. This paper looks at the Australian 2019 General Election and discusses a major Fake News example that occurred during that election. The paper will also describe the different types of social media data was collected during the study and also present the analysis of the data collected as well discussing the research findings including the ethical issues.

Covering Protests on Twitter: The Influences on Journalists’ Social Media Portrayals of Left- and Right-Leaning Demonstrations in Brazil

2019 ◽  
Vol 25 (2) ◽  
pp. 260-280 ◽  
Author(s):  
Rachel R. Mourão ◽  
Weiyue Chen
Keyword(s):  
Social Media ◽  
Social Movements ◽  
Mixed Methodology ◽  
Social Media Data ◽  
Media Portrayals ◽  
Media Sociology ◽  
Left And Right ◽  
The Right ◽  
Media Data ◽  
The Way

This study uses a media sociology approach to untangle how multiple influences shape the way journalists cover left- and right-leaning protests on social media. Several studies have investigated how reporters portray social movements, finding that news marginalizes protestors by focusing on spectacle and violent tactics to the detriment of their ideas. In this study, we turn to journalists’ Twitter accounts to analyze if these patterns are transferred to social media, as predicted by the literature on normalization of new affordances. Through a mixed methodology matching survey and social media data from 466 Brazilian journalists who tweeted about protests in 2013 and 2015, results revealed individual attitudes predicted coverage, indicating that social media was a space for personal, not professional, expression. Contrary to the literature, findings show that social media portrayals were more legitimizing during the left-leaning demonstrations than during the right-leaning elite-driven one. As a result, marginalizing patterns of protest coverage were challenged, not replicated, on Twitter. These findings suggest a limitation of the theory of normalization to explain how global journalists use social media.

scholarly journals DAKWAH DI TENGAH PANDEMI (STUDI TERHADAP RESPONS DAI DI MEDIA SOSIAL)

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Diajeng Laily Hidayati ◽  
Reza Fahlevi
Keyword(s):  
Social Media ◽  
Social Life ◽  
Virus Disease ◽  
Affective Response ◽  
Real Life ◽  
Face Mask ◽  
Positive Thinking ◽  
Social Media Data ◽  
The Government ◽  
Media Data

The Covid-19 (Corona Virus Disease-19) outbreak has managed to change the patterns of social life on society, including the change regarding the way Da’wa is performed; from conventional direct Da’wa to mediated Da’wa through internet. This article aims at describing responses of the Da’is (proselytizers) in social media pertaining to the spread of the Covid-19. This article applied qualitative method to analyse Da’wa contents related to Covid-19 on social media. Data were collected through observation and documentation. Findings show that there are at least three types of responses from the Da’is; cognitive, affective, and behavioural responses.  Cognitive response is manifested in the form of delivering information regarding Covid-19 from the general and medical perspective such as promoting frequent hand-washing, maintaining good hygiene, obeying the government measurements, maintaining healthy level of gratitude and praying to God to be saved from the outbreak. Affective response is manifested in the form of promoting empathy, positive thinking, and avoiding panic. Behavioural response is manifested in the form of giving real-life example such as performing online congregation (pengajian online), wearing face mask, applying appropriate disinfection, and helping those heavily affected by the outbreak.Keywords: Covid-19, Dai, responses, and social media. 

scholarly journals Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social Media Data (Preprint)

2020 ◽  
Author(s):  
Qiuyan Liao ◽  
Jiehu Yuan ◽  
Meihong Dong ◽  
Lin Yang ◽  
Richard Fielding ◽  
...  
Keyword(s):  
Social Media ◽  
Public Engagement ◽  
Latent Class ◽  
Early Stage ◽  
Government Agency ◽  
Instrumental Support ◽  
Social Media Data ◽  
The Government ◽  
Government Responsiveness ◽  
Media Data

BACKGROUND Effective risk communication about the outbreak of a newly emerging infectious disease in the early stage is critical for managing public anxiety and promoting behavioral compliance. China has experienced the unprecedented epidemic of the coronavirus disease (COVID-19) in an era when social media has fundamentally transformed information production and consumption patterns. OBJECTIVE This study examined public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage based on an analysis of data from Sina Weibo, a major social media platform in China. METHODS Weibo data relevant to COVID-19 from December 1, 2019, to January 31, 2020, were retrieved. Engagement data (likes, comments, shares, and followers) of posts from government agency accounts were extracted to evaluate public engagement with government posts online. Content analyses were conducted for a random subset of 644 posts from personal accounts of individuals, and 273 posts from 10 relatively more active government agency accounts and the National Health Commission of China to identify major thematic contents in online discussions. Latent class analysis further explored main content patterns, and chi-square for trend examined how proportions of main content patterns changed by time within the study time frame. RESULTS The public response to COVID-19 seemed to follow the spread of the disease and government actions but was earlier for Weibo than the government. Online users generally had low engagement with posts relevant to COVID-19 from government agency accounts. The common content patterns identified in personal and government posts included sharing epidemic situations; general knowledge of the new disease; and policies, guidelines, and official actions. However, personal posts were more likely to show empathy to affected people (χ<sup>2</sup><sub>1</sub>=13.3, <i>P</i>&lt;.001), attribute blame to other individuals or government (χ<sup>2</sup><sub>1</sub>=28.9, <i>P</i>&lt;.001), and express worry about the epidemic (χ<sup>2</sup><sub>1</sub>=32.1, <i>P</i>&lt;.001), while government posts were more likely to share instrumental support (χ<sup>2</sup><sub>1</sub>=32.5, <i>P</i>&lt;.001) and praise people or organizations (χ<sup>2</sup><sub>1</sub>=8.7, <i>P</i>=.003). As the epidemic evolved, sharing situation updates (for trend, χ<sup>2</sup><sub>1</sub>=19.7, <i>P</i>&lt;.001) and policies, guidelines, and official actions (for trend, χ<sup>2</sup><sub>1</sub>=15.3, <i>P</i>&lt;.001) became less frequent in personal posts but remained stable or increased significantly in government posts. Moreover, as the epidemic evolved, showing empathy and attributing blame (for trend, χ<sup>2</sup><sub>1</sub>=25.3, <i>P</i>&lt;.001) became more frequent in personal posts, corresponding to a slight increase in sharing instrumental support, praising, and empathizing in government posts (for trend, χ<sup>2</sup><sub>1</sub>=9.0, <i>P</i>=.003). CONCLUSIONS The government should closely monitor social media data to improve the timing of communications about an epidemic. As the epidemic evolves, merely sharing situation updates and policies may be insufficient to capture public interest in the messages. The government may adopt a more empathic communication style as more people are affected by the disease to address public concerns.

Post, Mine, and Be Disturbed: Social Media Data Mining

PsycCRITIQUES ◽  
2016 ◽  
Vol 61 (51) ◽  
Author(s):  
Daniel Keyes
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Media Data ◽  
Media Data
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