In this analysis, I examine the statistical significance of attitude changes towards various political objects before and after the MLK assassination, stratified by race. Using the dataset of affect percentages and sample sizes reported in the article, I perform chi-squared tests on contingency tables to assess significant shifts in positive and negative attitudes for each political object and racial group. The results are presented in tables and visualized through bar charts, highlighting statistically significant changes (p < 0.05). Additionally, I conduct polarization analyses using both variance-based methods (Levene’s test) and more advanced techniques (polarization index, kurtosis, and Kolmogorov-Smirnov tests) to examine changes in the spread and shape of attitude distributions. For significant changes, I create density ridge plots to visualize the shifts in attitude distributions. This approach combines methods available in 1969 with modern techniques to provide a comprehensive view of attitude changes and potential polarization effects following the assassination. The findings regarding the minimal effect on white respondents are largely aligned with Hofstetter’s article. No statistically significant changes in positive or negative affect were observed among white respondents for any political object. The advanced polarization analysis confirms this, showing no significant changes in the distribution of white attitudes (all KS p-values = 1). For Black respondents, the most notable change was towards the police. This change manifested in multiple ways: a significant increase in negative affect (from 3.7% to 31.0%, p = 0.01), a substantial but not statistically significant decrease in positive affect (from 88.9% to 58.6%, p = 0.274), a significant increase in opinion polarization as measured by variance ratio (2.450, p < 0.01), and a significant change in the overall distribution of attitudes (KS p-value = 0.0154). The polarization for police attitudes among Black respondents increased dramatically indicating a substantial increase in polarization. Other changes in Black respondents’ attitudes were observed but were not statistically significant.

The followin chart, based on data from the Tunisian National Institute of Statistics (INS) and the International Labour Organization (ILO) illustrate the evolution of the unemployment rate among young men in Tunisia between 1990 and the second quarter of 2024. The data reveals a general upward trend, with notable peaks in 2011 (coinciding with the revolution) and 2020 (during the COVID-19 pandemic). Furthermore, a sharp increase is observed towards the end of the analyzed period, culminating in a record-high unemployment rate in the second quarter of 2024.

The analysis aims to study the effect of the perception of corruption among business executives (Q114) on the preference for private versus state ownership of businesses (Q107). By fitting both linear and generalized linear models, we seek to understand if and how perceptions of corruption influence individuals' opinions on business ownership models in Tunisia. The models also control for other covariates like urban/rural status (H_URBRURAL), interview date (J_INTDATE), age (Q262), and sex (Q260). The analysis reveals a significant positive association between the perception of corruption among business executives and the preference for government ownership of businesses. This relationship remains robust even when controlling for other variables, including urban/rural status, interview date, age, and sex. Specifically, individuals who perceive higher levels of corruption are more likely to prefer government ownership. Urban residents and older individuals also show a stronger preference for government ownership. Additionally, the data suggests that over time, preferences might be gradually shifting towards government ownership. These findings highlight the impact of corruption perceptions on ownership preferences and underscore the importance of addressing corruption to influence public opinion on economic policies.

Source: Ipsos Talan survey for France Télévisions, Radio France, and Public Sénat Footnote: Data derived from a representative poll conducted from June 27 to 28, 2024, among 10,286 people, constituting a representative sample of the French electoral population aged 18 and over.

The survey was conducted on April 3–10, 2018.38 The sample was screened to include only those who consider themselves evangelical and/or bornagain Christians. We adopted self-identification as a standard by which we identify evangelical and born-again respondents. We deliberately avoided narrowing the definition to white evangelicals only (as some do) and included evangelicals of all races (about 40% of the total population are nonwhite). We also chose not to utilize the four principles of evangelism as screening questions for inclusion, as the National Association of Evangelicals suggests. As Gregory Smith et al. have shown, the self-identification method among American Protestants can be used and reliably substituted as an effective measurement of this religious identity.39 A demographically balanced online panel was used. Maximum quotas and slight weights were used for gender, region, age, ethnicity, and education to more accurately reflect the evangelical population in the United States (as defined by the 2014 Pew Religious Landscape Survey). 2,754 respondents started the survey, 1,694 were screened out by quotas or the screening criteria, and 60 were incomplete or spoiled. The completed sample is 1,000 surveys. The sample provides 95% confidence that the sampling error does not exceed plus or minus 3.27%, accounting for weights. Source: Inbari & Bumin (2023) Christian Zionism in the Twenty-First Century: American Evangelical Opinion on Israel

This map illustrates the countries utilizing Bell 212 helicopters, highlighting the widespread adoption across diverse geographic and political landscapes. Source: The Military Balance 2023 IISS.

This study by investigates the effects of geopolitical events on trends in antisemitism and Islamophobia. Using data from Google Trends, various media sources, and FBI hate crime reports, the research identifies increased public interest and reported hate crimes during periods of conflict, notably following the 2023 war. Statistical analyses, including t-tests and regression discontinuity designs, show notable shifts in public concern and behavior around the 2016 U.S. presidential election.

Prior to Modi's tenure, India-Israel defense ties were low-key, primarily due to India's strategic caution and its traditional support for the Palestinian cause. Modi's election brought a change in this approach, with a more open acknowledgment and public endorsement of the relationship. Detailed timeline: 1992: Establishment of Full Diplomatic Relations - India officially established full diplomatic relations with Israel in January 1992, paving the way for military and strategic ties. 1996-1998: Early Defense Deals - The first major defense deal between India and Israel occurred in 1996, with India purchasing the Barak-1 naval air defense system. This was followed by several other defense procurements. 2003: Phalcon AWACS Deal - In 2003, India signed a deal with Israel for the Phalcon Airborne Warning and Control System (AWACS), a significant step in airborne surveillance and intelligence. 2009: Spyder Missile System - In 2009, India acquired the Spyder missile system from Israel, enhancing its air defense capabilities. 2017: Major Spike Missile Deal - India signed a large-scale contract in 2017 to acquire Spike anti-tank guided missiles from Israel, although the deal faced some initial uncertainty before being finalized. 2017: Visit by Indian Prime Minister - Indian Prime Minister Narendra Modi visited Israel in July 2017, marking the first visit by an Indian Prime Minister to Israel. This visit was seen as a significant step in bolstering bilateral defense ties. 2018-Present: Growing Defense Cooperation - From 2018 onwards, India-Israel military cooperation has continued to grow, with several joint ventures and collaborative projects in defense technology, including drone technology, cybersecurity, and intelligence sharing. 2020: Emergency Procurement during Border Tensions - Amidst border tensions with China in 2020, India made an emergency procurement of assault rifles and other equipment from Israel.

Contrary to the claim that Palestine distracts' Arabs from their domestic politics, Google search data shows that the 2023 war on Gaza didn't displace attention to domestic outlets. The effect on attention to popular audiovisual media (Mosaique FM, Diwan FM, and Shems FM) is statistically insignificant. However, the effect on internet users' interest in Arabic-speaking international media covering Israel's military campaign on Gaza did increase for both Qatar-based Al Jazeera and Saudi-based Al Arabiya. This suggests that the consumption of media increases when Israel intensifies its military action against Palestinians without affecting domestic media consumption.

This bar chart provides a visual representation of American military deaths across various conflicts, from the American Revolutionary War to the Iraq War. The data highlights the stark differences in death tolls, reflecting the varying scales, durations, and intensities of these wars. Notable peaks include the Civil War, World War II, and the Vietnam War, which collectively underscore the substantial human cost associated with major military engagements.

The plot presents the trends in public attitudes towards military rule in Niger from 2013 to 2022. The attitudes are categorized into three groups: "Disapprove", "Neither Approve Nor Disapprove", and "Approve". Here are the observed trends: Disapproval of Military Rule: There is a noticeable decline in the disapproval of military rule over the years. Starting at a high of approximately 57.6% in Spring 2013, the percentage of those who disapprove military rule increased to its peak of about 72.8% in Spring 2015. It then began a downward trend, dropping to about 60.5% in Spring 2018, then to approximately 61.9% in Fall 2020. The most significant drop appears between Fall 2020 and Summer 2022, where the disapproval rate decreased to about 43.8%. The linear regression line also confirms this overall declining trend. Approval of Military Rule: On the contrary, the approval of military rule exhibits a fluctuating trend over the observed years. It started at approximately 30% in Spring 2013, then dipped to a low of about 18.9% in Spring 2015. It then experienced a surge to about 35.8% in Spring 2018 before slightly decreasing to 31.3% in Fall 2020. Notably, by Summer 2022, the approval rate increased significantly to about 48.5%, surpassing the disapproval rate for the first time in the observed period. The linear regression line indicates an overall upward trend. Neither Approve Nor Disapprove: The percentage of respondents who neither approve nor disapprove of military rule remained relatively low and stable throughout the period. It started at about 10.3% in Spring 2013 and decreased to about 6.6% in Spring 2015. It further decreased to 2.5% in Spring 2018, slightly rose to 5.4% in Fall 2020, and remained almost the same at 5.2% in Summer 2022. Overall, the plot suggests a shifting public opinion in Niger, with a decreasing trend in disapproval and an increasing trend in approval of military rule over time.

This visualization showcases the fielding dates for the Arab Barometer Wave VI survey across several MENA region countries. Each country has three sets of fielding dates, represented by segments on the timeline. The start of each segment is marked with a black dot, while the end is marked with an orange dot. This visual representation helps us understand the chronological progression of the surveys across different countries. Note: Iraq did not participate in the first two parts of the survey, and hence, only appears in the third part on the timeline plot.

This plot presents a seasonal and trend decomposition of the media visibility of UGTT using the Loess method. The time series data has been broken down into three components: seasonal, trend, and random. Seasonal Component: The top panel after the raw data shows the seasonal component of the time series. This represents the regular pattern of fluctuations in the data that repeat with the same length of cycle. In this case, the cycle is one year. The seasonal component can help identify times of the year when media visibility is consistently higher or lower. Trend Component: The second panel shows the trend component. This represents the underlying direction that the time series is taking, ignoring any seasonality. In this case, it appears that there is a general upward trend in media visibility over time, though with some periods of decline. Random Component: The third panel shows the random (or irregular, or remainder) component. This is what remains after the seasonal and trend components have been removed from the original time series. It represents irregular changes that are not accounted for by the seasonality or the trend. A vertical red dashed line is drawn on July 25, 2021.

This network visualization represents visits made by senior Chinese military officers such as the PRC's Defense Minister, Chief of General Staff (now Chief of the Joint Staff), Deputy Chief of General Staff (now Deputy Chief of the Joint Staff). Data Source: Chinese Military Diplomacy, 2003–2016

This map represents visits made by senior Chinese military officers such as the PRC's Defense Minister, Chief of General Staff (now Chief of the Joint Staff), Deputy Chief of General Staff (now Deputy Chief of the Joint Staff). Data Source: Chinese Military Diplomacy, 2003–2016

This network visualization represents visits made by senior Chinese military officers such as the PRC's Defense Minister, Chief of General Staff (now Chief of the Joint Staff), Deputy Chief of General Staff (now Deputy Chief of the Joint Staff). Data Source: Chinese Military Diplomacy, 2003–2016

Source: Google Trends, Webradar

The plot shows the seasonal component of terrorism trends in Tennessee from May 2009 to May 2023. The seasonal component represents the regular pattern of variation in the data that repeats itself over fixed intervals, in this case, every year. The plot indicates that there is a clear seasonal pattern in the data, with higher rates of interest in terrorism occurring in the summer months (June to August) and lower rates in the winter months (December to February). The seasonal component also shows some irregularities in the data, particularly in the summer of 2013, when the rate of interest in terrorism was unusually high, and in the winter of 2020-2021, when the rate was lower than expected. Overall, the plot provides insights into the seasonality of terrorism trends in Tennessee and can help identify periods of increased or decreased risk. From the plot, we can observe that there is a clear upward trend in terrorism rates in Tennessee from 2009 to around 2014, followed by a decrease in rates until around 2017, and then a relatively stable trend from 2017 to 2023. The trend suggests that the rate of terrorism in Tunisia has increased in the long-term, but with some fluctuations in the short-term.

The decomposition plot displays the various components of the Google Trends data related to war from 2004 to 2023. The plot is divided into four sections: the original time series, the seasonal component, the trend component, and the random component (residuals). The original time series demonstrates a pattern of fluctuating interest over the years, with some noticeable peaks and troughs. The seasonal component highlights the cyclical nature of the interest, revealing a recurring pattern throughout each year. The trend component shows a general decline in interest over time, while the random component captures the unexplained variations in the data.

Source: Global Terrorism Database (GTD) University of Maryland National Consortium for the Study of Terrorism and Responses to Terrorism Summary statistics: Islamic terrorist attacks pre-9/11: 31 Islamic terrorist attacks post-9/11: 60 Non-Islamic terrorist attacks pre-9/11: 1991 Non-Islamic terrorist attacks post-9/11: 432

Source: Global Terrorism Database (GTD) University of Maryland National Consortium for the Study of Terrorism and Responses to Terrorism Summary statistics: Islamic terrorist attacks pre-9/11: 55 Islamic terrorist attacks post-9/11: 64 Non-Islamic terrorist attacks pre-9/11: 225 Non-Islamic terrorist attacks post-9/11: 1398

During its sixth and seventh waves, the World Values Survey asked: Many things are desirable, but not all of them are essential characteristics of democracy. For each of the following things listed below, please indicate how essential you think it is as a characteristic of democracy. Please use the 1 to 10, scale where 1 means it is “not at all an essential characteristic of democracy” and 10 means it is definitely “an essential characteristic of democracy.” The army takes over when the government is incompetent.