Public Emotional Response on the Black Lives Matter Movement in the Summer of 2020 as Analyzed Through Twitter

Patnaude, Laura; Lomakina, Carolina Vásquez; Patel, A.; Bizel, Gulhan

doi:10.5539/ijms.v13n1p69

Cited by 7 publications

(7 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is interesting to observe that r/news and r/worldnews correlate positively with user attention compared to r/politics. This could be a sign that users interested in BLM are rather looking for an international perspective on BLM (r/news, r/worldnews) as it is a worldwide protest [ 21 ] compared to solely reading BLM news related to the US context (r/politics).…”

Section: Discussionmentioning

confidence: 99%

“…The BLM movement began with a social media hashtag after the acquittal of the man charged in the shooting death of Black teenager Trayvon Martin in Florida in 2012 [ 21 ], grew nationally in 2014 after the deaths of Michael Brown in Missouri and Eric Garner in New York [ 19 ], and was reignited by the death of George Floyd, a Black man murdered by a white police officer on May 25, 2020, in Minneapolis [ 21 ]. People all over the world went into the streets to show solidarity and join the movement’s fight against “racial injustice and police brutality” [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit

Henn,

Posegga

2023

PLoS ONE

View full text Add to dashboard Cite

Portrayals of violence are common in contemporary media reporting; they attract public attention and influence the reader’s opinion. In the particular context of a social movement such as Black Lives Matter (BLM), the portrayal of violence in news coverage attracts public attention and can affect the movement’s development, support, and public perception. Research on the relationship between digital news content featuring violence and user attention on social media has been scarce. This paper analyzes the relationship between violence in online reporting on BLM and its effect on user attention on the social media platform Reddit. The analysis focuses on the portrayal of violence in images used in BLM-related digital news coverage shared on Reddit. The dataset is comprised of 5,873 news articles with images. The classification of violent images is based on a VGG19 convolutional neural network (CNN) trained on a comprehensive dataset. The results suggest that what significantly affects user attention in digital news content is not the display of violence in images; rather, it is negative article titles, the news outlet’s political leanings and level of factual reporting, and platform affordances that significantly affect user attention. Thus, this paper adds to the understanding of user attention distributions online and paves the way for future research in this field.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit

Henn,

Posegga

2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…One study suggests that a majority of those in the U.S. support law enforcement use of genealogy websites [61]. Our work hopes to gauge current public opinion on the practice, particularly in the wake of expanded government use of health data for public safety and well-being, and the growing discourse surrounding the role of law enforcement in communities [21,74,104,105].…”

Section: Item 2: "Dna Testing Companies Sharing Their Customers' Gene...mentioning

confidence: 98%

Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021

Goetzen

Dooley²,

Redmiles

2022

PoPETs

View full text Add to dashboard Cite

People’s privacy sentiments influence changes in legislation as well as technology design and use. While single-point-in-time investigations of privacy sentiment offer useful insight, study of people’s privacy sentiments over time is also necessary to better understand and anticipate evolving privacy attitudes. In this work, we build off of a 2019 Pew Research study and use repeated cross-sectional surveys (n=6,676) from 2019, 2020, and 2021 to model the sentiments of people in the U.S. toward collection and use of data for government- and health-related purposes. After the onset of COVID-19, we observe significant decreases in respondent acceptance of government data use and significant increases in acceptance of health-related data uses. While differences in privacy attitudes between sociodemographic groups largely decreased over this time period, following the 2020 U.S. national elections, we observe some of the first evidence that privacy sentiments may change based on the alignment between a user’s politics and the political party in power. Our results offer insight into how privacy attitudes may have been impacted by recent events and allow us to identify potential predictors of changes in privacy attitudes during times of geopolitical or national change.

show abstract

“…Rezapour (2018) examinedthrough linguistic features and sentimentsthe language and vocabulary relating to this movement that were used on Twitter and traditional news articles to discover parallels and variations in a speech. Other studies were devoted to inspecting the public emotional response and attitude toward the BLM movement using either basic lexicon analysis (Patnaude et al, 2021) or ML and DL techniques (Peng et al, 2022). SA was also brought into play to investigate opinions and leadership roles during SMs.…”

Section: Social Movements and Sentiment Analysismentioning

confidence: 99%

Sentiment analysis of the Algerian social movement inception

Laifa

Mohdeb²

2023

DTA

View full text Add to dashboard Cite

PurposeThis study provides an overview of the application of sentiment analysis (SA) in exploring social movements (SMs). It also compares different models for a SA task of Algerian Arabic tweets related to early days of the Algerian SM, called Hirak.Design/methodology/approachRelated tweets were retrieved using relevant hashtags followed by multiple data cleaning procedures. Foundational machine learning methods such as Naive Bayes, Support Vector Machine, Logistic Regression (LR) and Decision Tree were implemented. For each classifier, two feature extraction techniques were used and compared, namely Bag of Words and Term Frequency–Inverse Document Frequency. Moreover, three fine-tuned pretrained transformers AraBERT and DziriBERT and the multilingual transformer XLM-R were used for the comparison.FindingsThe findings of this paper emphasize the vital role social media played during the Hirak. Results revealed that most individuals had a positive attitude toward the Hirak. Moreover, the presented experiments provided important insights into the possible use of both basic machine learning and transfer learning models to analyze SA of Algerian text datasets. When comparing machine learning models with transformers in terms of accuracy, precision, recall and F1-score, the results are fairly similar, with LR outperforming all models with a 68 per cent accuracy rate.Originality/valueAt the time of writing, the Algerian SM was not thoroughly investigated or discussed in the Computer Science literature. This analysis makes a limited but unique contribution to understanding the Algerian Hirak using artificial intelligence. This study proposes what it considers to be a unique basis for comprehending this event with the goal of generating a foundation for future studies by comparing different SA techniques on a low-resource language.

show abstract

Public Emotional Response on the Black Lives Matter Movement in the Summer of 2020 as Analyzed Through Twitter

Cited by 7 publications

References 2 publications

Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit

Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit

Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021

Sentiment analysis of the Algerian social movement inception

Contact Info

Product

Resources

About