This dataset covers the use of social media to influence politics by promoting propaganda, advocating controversial viewpoints, and spreading disinformation. Influence efforts are defined as: (i) coordinated campaigns by a state, or the ruling party in an autocracy, to impact one or more specific aspects of politics at home or in another state, (ii) through media channels, including social media, by (iii) producing content designed to appear indigenous to the target state. Our data draw on more than 1000 media reports and 500 research articles/reports to identify IEs, track their progress, and classify their features. The data cover 78 foreign influence efforts (FIEs) and 25 domestic influence efforts (DIEs)—in which governments targeted their own citizens—against 51 different countries from 2011 through early-2021. The Influence Effort dataset measures covert information campaigns by state actors, facilitating research on contemporary statecraft.

The 2013 Urban Influence Codes form a classification scheme that distinguishes metropolitan counties by population size of their metro area, and nonmetropolitan counties by size of the largest city or town and proximity to metro and micropolitan areas. The standard Office of Management and Budget (OMB) metro and nonmetro categories have been subdivided into two metro and 10 nonmetro categories, resulting in a 12-part county classification. This scheme was originally developed in 1993. This scheme allows researchers to break county data into finer residential groups, beyond metro and nonmetro, particularly for the analysis of trends in nonmetro areas that are related to population density and metro influence. An update of the Urban Influence Codes is planned for mid-2023.

According to a survey on social media in February 2022, the majority of Indonesians have bought items after seeing them on social media, accounting for approximately 62.1 percent of the respondents. As of October 2022, Facebook has the largest market share among other social media platforms in the country.

Rachmad, Yoesoep Edhie. 2023. Influence-Driven Consumption Theory. Tangier Qasbah Kitab Tanbit, Tanbit Khas 2023. https://doi.org/10.17605/osf.io/n5cv2

The Influence-Driven Consumption Theory, developed by Yoesoep Edhie Rachmad and outlined in his 2023 publication "Tangier Qasbah Kitab Tanbit, Tanbit Khas," explores the dynamics of how social influence shapes consumer behavior, particularly in the context of modern digital environments. Rachmad's research, which he began in 2016, delves into the ways in which consumer choices are increasingly driven by social networks, influencers, and online communities. This theory emerges from the understanding that in the digital age, consumers are not isolated decision-makers. Instead, they are embedded in social networks that provide continuous streams of information and opinion that significantly shape their purchasing behaviors. Rachmad observed that this influence is not merely incidental but a fundamental component of how products and services are marketed and consumed in contemporary society. The Influence-Driven Consumption Theory posits that social influence operates through various mechanisms, including direct recommendations from friends and family, the persuasive power of influencers on platforms like Instagram and YouTube, and through more subtle cues like the popularity and ratings of products on e-commerce sites. These influences combine to form a powerful force that can drive consumer decisions more effectively than traditional advertising. Rachmad concludes that understanding the pathways and effects of social influence is crucial for businesses looking to effectively market their products. He suggests that marketers should focus on creating strategies that harness the power of social influence, such as developing strong relationships with key influencers, encouraging social sharing and reviews, and using social proof as a central component of marketing campaigns. He recommends that companies invest in analytics to better understand the social dynamics of their target markets and tailor their marketing efforts to leverage these insights. Additionally, Rachmad emphasizes the importance of authenticity and trustworthiness, noting that consumers are increasingly savvy about influence tactics and will reject efforts that seem disingenuous. Overall, the Influence-Driven Consumption Theory provides a sophisticated framework for understanding the increasingly complex web of influences that affect consumer purchases. It offers critical insights for marketers aiming to adapt to the realities of a marketplace where decisions are deeply interwoven with social context and where influence is a key currency.   Table of Contents Rachmad, Yoesoep Edhie. 2023. "Influence-Driven Consumption Theory." Tangier Qasbah Kitab Tanbit, Tanbit Khas. [DOI: https://doi.org/10.17605/osf.io/n5cv2]

Chapter 1: Introduction to Influence-Driven Consumption Understanding the Impact of Social Influence...............3 From Individual to Social Decision-Making................19 The Evolution of Digital Influence...............................35 Chapter 2: Foundations of the Theory Defining Social Influence in Modern Consumption........53 Key Concepts and Mechanisms..................................71 Historical Context and Evolution of Influence Tactics...89 Chapter 3: Mechanisms of Social Influence Direct Recommendations and Word-of-Mouth..............107 Influencer Marketing on Social Media Platforms.............123 Social Proof and the Role of Ratings and Reviews...........141 Chapter 4: The Digital Environment and Social Influence The Rise of Online Communities.................................159 How Social Media Shapes Consumer Perceptions...........175 E-commerce as a Platform for Influence........................193 Chapter 5: The Psychology Behind Influence-Driven Consumption Cognitive Biases in Social Decision-Making..................211 The Power of Trust and Authority................................227 Emotional Triggers in Online and Offline Influence...........243 Chapter 6: Influence Strategies for Marketers Building Strong Relationships with Key Influencers........261 Utilizing User-Generated Content for Authentic Marketing....279 Incorporating Social Proof in Advertising Campaigns.........297 Chapter 7: Analytics and Measuring Social Influence Tracking Consumer Interactions and Influencer Impact.....315 Leveraging Big Data for Insights on Social Dynamics.........333 Using Sentiment Analysis to Gauge Consumer Opinion.......349 Chapter 8: Challenges and Ethical Considerations Navigating Authenticity in the Age of Social Influence.......367 The Risks of Overusing Influencer Marketing...................385 Dealing with Fake Reviews and Manipulated Social Proof...403 Chapter 9: Case Studies in Influence-Driven Consumption Successful Campaigns Utilizing Social Influence..............421 Lessons from Failed Attempts at Harnessing Influence.......439 Industry-Specific Examples: Fashion, Technology, and Food...457 Chapter 10: The Future of Influence-Driven Consumption Emerging Trends in Social Influence and Consumer Behavior...475 The Evolving Role of AI in Predicting Consumer Trends......493 Integrating New Technologies for Enhanced Influence Marketing...511

Appendices Appendix A: Glossary of Key Terms and Concepts....................529 Appendix B: Methodologies for Measuring Social Influence........543 Appendix C: Tools and Software for Analyzing Social Networks....557 References Citations and Influential Works in the Field...........................571 Index Comprehensive Index of Topics Covered...................................589

AUTHOR PROFILE
In 2016, the author earned the title of Doctor of Humanity, hold a Ph.D. in Information Technology and a DBA in General Management. Since 2016, the author has been teaching at international universities in Malaysia, Singapore, Thailand, and the USA. In 1999, the author founded the Education Training Centre (ETC), an organization dedicated to providing educational services and social support for the underprivileged. This organization offers shelter homes for children in need of a safe place to live and drop-in schools for those who need to continue their education. The ETC is also involved in research aimed at advancing science, which led to the author earning the title of Professor and joining the WPF. Additionally, the author is actively involved in global social development programs through the United Nations. They are a member of the UN Global Compact (id-137635), the UN Global Market (id-709131), and the UN ECOSOC (id-677556). The author has served as a reviewer for several international journals and book chapters, and has written numerous books and articles on a wide range of topics including Philosophy, Economics, Management, Arts and Culture, Anthropology, Law, Psychology, Education, Sociology, Health, Technology, Tourism, and Communication.

In the rapidly evolving digital era, understanding how influence and information spread across various digital platforms has become increasingly crucial. Advances in technology and social media have transformed how we communicate, share information, and build relationships. Digital Influence Theory (DIT), for example, explains how individuals or entities can influence others' behaviors and decisions through digital technology. Network Influence Theory (NIT) explores how influence spreads through the structure of social networks. Trust has become a key factor in modern marketing, as highlighted by Trust-Based Marketing Theory (TBMT), which underscores the importance of building and leveraging trust to influence consumer decisions. Engagement Influence Theory (EIT) and Interactive Marketing Theory (IMT) emphasize that active user engagement and interaction with content can significantly amplify influence. Meanwhile, Authenticity and Credibility Theory (ACT) asserts that authenticity and credibility are crucial for effective influence. Personalized Influence Theory (PIT) highlights the importance of personalization in communication and marketing to enhance the relevance and impact of messages. By understanding the commonalities among these theories, marketers and communicators can design more effective strategies to build and spread influence in the ever-evolving digital world. These commonalities include a focus on influence, the importance of digital and social media, user engagement, trust and credibility, personalization and relevance, the use of technology and digital tools, social interaction, and strategy and implementation. Each theory provides a framework or guide for designing effective strategies to build and spread influence. They emphasize the importance of understanding the audience, creating quality content, and using the right platforms to achieve marketing and communication goals. By understanding the differences among these theories, marketers and communicators can more effectively design strategies that align with their goals and audience characteristics. Companies can select and apply the most relevant theory to specific contexts and objectives in digital marketing and communication. The book 'Diverse Paths to Influence: Comparing Digital Influence Theories' by Yoesoep Edhie Rachmad delves into these theories, offering insights and practical applications for enhancing influence in the digital age.

According to a survey on social media influencers conducted by Rakuten Insight in May 2023, approximately 68 percent of Indonesian respondents stated that they had purchased an item or product because it had been endorsed by an influencer. The same survey found that the majority of Indonesian respondents followed at least one influencer on social media.

This dataset contains information on the cluster characteristics, health effect estimates, and the meta-regression results. This dataset is associated with the following publication: Baxter, L., J. Crooks, and J. Sacks. Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities. ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 16(1): 1-8, (2017).

The data presents mother tongue and social media influence on second language learners' English proficiency. English is used as a medium for global communication, education, business, and research. Subsequently, universities in more than 130 countries determine prospective students' level of proficiency through English competency tests such as IELTS and TOEFL. This adds an additional burden to Grade 12 English FAL learners to be more proficient. The study was conducted through a qualitative approach with an interpretivist paradigm. It was theoretically framed on the Linguistic Interdependence Theory of Cummins(1978). The study adhered to Ethics committee approval which advocates for voluntary participation and anonymity of participants to protect identity.

Descriptive statistics of percent hard (high-effort) choices (left) and reaction time (right) during each of the six nested conditions.Percentage of Hard Choices and Reaction Time During Influence Conditions.

The baseline survey in Tajikistan captures data in the Feed the Future Zones of Influence (ZOI), comprised of 12 of the 24 districts in Khatlon province. A total of 2,000 households in the ZOI were surveyed for the PBS data collection activity. These households are spread across 100 standard enumeration areas in the targeted districts. The survey is comprised of ten CSV files: a children's file, a household-level file, a household member level file, a women's file, several files describing consumption, and two files used to construct the Women's Empowerment in Agriculture Index. This dataset contains variables from Module E, the Household Consumption Expenditures module used to calculate poverty and expenditure indicators.

The adopted Sacramento General Plan includes a policy to work with the Sacramento Local Agency Formation Commission (SLAFCO) to adjust the City's Sphere of influence to be in conformity with the City's Annexation Policy. The Sphere of Influence (SOI) is defined as "a plan for the probable ultimate physical boundaries and service area of a local government agency." All proposed annexations must be located within the City's adopted SOI before they can be considered by SLAFCO. Contact GIS at: sacgis@cityofsacramento.org

Scientific influence, or the capacity of ideas and concepts to shape future research, is crucial to developing and disseminating knowledge and sustained innovation. Using nearly 240 million scientific papers published between 1990 and 2023 from OpenAlex to construct international networks of influence, I demonstrate that discursive influence, which represents what global scientific communities consider important and worthy of investigation, is disproportionately and increasingly concentrated in a small group of resource-wealthy countries, including the United States, Canada, Western Europe, and East Asia, in comparison to attributional influence. This concentration raises issues of equity and innovation in global scientific discourse, perhaps narrowing research perspectives, exacerbating biases, and creating echo chambers that stifle innovation and marginalize contributions from countries that are peripheral to global scientific discourse. Findings underscore the need for policies that ensure diverse and inclusive global research enterprises.

Context

Discover 1000 Top Ranked Influencers by Type and Category of Influence in United States.

Acknowledgements

Data source: https://starngage.com/app/global/influencer/ranking/united-states

This data archive contains the underlying data for the conference publication entitled "Using Finite Element Analysis to Influence the Infill Design of Fused Deposition Modelled Parts". The paper has been accepted for publication in the journal: Progress in Additive Manfacturing.

The paper describes a process that uses results attained from Finite Element Analysis (FEA) to influence the design of the internal structure (i.e. infill) of 3D printed parts by locally varying the composition of the infill based upon the associated stress values.

The graph shows the share of consumers who think the entertainment industry has too much or too little influence in Washington, D.C. and politics in the United States as of February 2018. During the survey, 38 percent of respondents stated that they thought the entertainment industry had too much influence in Washington, D.C. and politics.

The .zip file contains the input data, the results and the scripts used for the paper "Influence of input reflectance values on climate-based daylight metrics using sensitivity analysis", accepted for publication in the Journal of Building Performance Simulation.
Series of random reflectance values were generated using the Method of Morris sampling strategy and were later used as input in the Climate-Based Daylight Modelling evaluations carried out with five different simulation techniques. The results from the simulations were further analysed with the Method of Morris to understand the sensitivity of the models to the selected reflectance values.
Input and results are all stored in .txt format. The scripts were created for the use with iPython notebooks. The 3D models of the classrooms used for this work are available for downloading from the GitHub link provided here.

The IZ kmax datasets contains all the design information and results of the influence zone evaluation conducted in the Gallet et al. (2024) journal article "Influence zone of continuous beam systems (doi.org/10.1016/j.istruc.2024.107069). The dataset is publicly available on a CC-BY-4.0 licence. In addition to the datasets, a simple python script demonstrating the use of Algorithm 1 and 2 developed in the Gallet et al. (2024) journal article is made available.There are 5 files in this directory:critical_load_arrangement_algorithms_and_example.pyIZ_kmax_set1_zero_variation.csvIZ_kmax_set2_low_variation.csvIZ_kmax_set3_medium_variation.csvIZ_kmax_set4_high_variation.csvClick "Download all" (button at the top) to download the files.

The files contain the replication code and data for "Anti-Democratic Influence: The Effect of Citizens United on State Democratic Performance."

NCALM Seed. PI: Celso Ferreira, Texas A&M University. The survey area consists of a long rectangular polygon located on the Gulf Coast 25 kilometers east of Corpus Christi, TX. Lidar data were collected to investigate the influence of dunes and barrier islands on hurricane surge in Corpus Christi, Texas.