 | |
| Type | Research institute |
|---|---|
| Established | 2015 |
| Director | Sean Young, PhD |
| Location | , |
| Website | http://predictiontechnology.ucla.edu/ |
The University of California, Institute for Prediction Technology (UCIPT) is a multidisciplinary organization seeking to accelerate technological research and innovations to predict human behavior and real-world events.
Groundwork for UCIPT began in 2013 with a partnership with the UCLA Center for Digital Behavior. In 2014, research results from public health studies by the Institute's research team began to appear in newspapers, [1] [2] blogs, [3] [4] and other media outlets. [5] [6] In January 2015, UCIPT was formally established by Sean Young, who serves as its executive director. Initial funding for the organization was provided by a University of California (UC) President's Research Catalyst Award. [7]
UCIPT has research leaders at four university campuses: UCLA, UC San Diego, UC Santa Cruz, and UC Irvine; UCLA is the hosting institution.
Technologies such as social media, wearable devices, and online search engines continuously generate large volumes of public data (social “big data”). UCIPT develops tools to analyze these data to inform public and private sector efforts to solve real-world problems. Areas of focus include public health, finance, cybersecurity, consumer products, politics, and poverty. As of 2016, the primary work of the Institute has progressed in the field of public health, particularly in HIV prevention and detection. [8] [9]
1. Big data infrastructure
UCIPT is developing a new open-source platform for ingesting, storing, indexing, querying, and analyzing vast quantities of data. Projects combine ideas from three areas (semi-structured data, parallel databases, and data-intensive computing) in order to create an open-source platform that scales by running on large, shared-nothing commodity computing clusters. An example of work in this area is AsterixDB, which grew out of a collaborative grant awarded by the National Science Foundation to UC Irvine professor and UCIPT member Michael Carey. [10]
2. Machine learning models
UCIPT is working to optimize machine learning models that can improve the accuracy and speed of supervised and unsupervised learning. Biomedical applications, primarily to uncover hidden patterns and correlations within big data, are also being undertaken by UCIPT researchers.
3. Applications to solve real-world problems
UCIPT researchers have developed platforms to analyze social media data that allow real-time predictions about future events (e.g., crime). [11] [12] James H. Fowler, a member of UCIPT known for his work on social networks and genopolitics, studies predictors of political opinion as well as public health issues. Sean Young has used social media technologies to predict trends in HIV transmission. [13] Other studies generated by UCIPT focusing on the well-being of transgender persons, [9] [14] wearable technology, [15] and substance use [16] are ongoing.
Public health surveillance is, according to the World Health Organization (WHO), "the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice." Public health surveillance may be used to track emerging health-related issues at an early stage and find active solutions in a timely manner. Surveillance systems are generally called upon to provide information regarding when and where health problems are occurring and who is affected.
Social media are interactive technologies that facilitate the creation and sharing of content, ideas, interests, and other forms of expression through virtual communities and networks. While challenges to the definition of social media arise due to the variety of stand-alone and built-in social media services currently available, there are some common features:
Social television is the union of television and social media. Millions of people now share their TV experience with other viewers on social media such as Twitter and Facebook using smartphones and tablets. TV networks and rights holders are increasingly sharing video clips on social platforms to monetise engagement and drive tune-in.
Adolescent health, or youth health, is the range of approaches to preventing, detecting or treating young people's health and well-being.
The sociology of the Internet involves the application of sociological or social psychological theory and method to the Internet as a source of information and communication. The overlapping field of digital sociology focuses on understanding the use of digital media as part of everyday life, and how these various technologies contribute to patterns of human behavior, social relationships, and concepts of the self. Sociologists are concerned with the social implications of the technology; new social networks, virtual communities and ways of interaction that have arisen, as well as issues related to cyber crime.
Reality mining is the collection and analysis of machine-sensed environmental data pertaining to human social behavior, with the goal of identifying predictable patterns of behavior. In 2008, MIT Technology Review called it one of the "10 technologies most likely to change the way we live."
Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity may lead to a higher false discovery rate. Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.
The social data revolution is the shift in human communication patterns towards increased personal information sharing and its related implications, made possible by the rise of social networks in the early 2000s. This phenomenon has resulted in the accumulation of unprecedented amounts of public data.
Since the arrival of early social networking sites in the early 2000s, online social networking platforms have expanded exponentially, with the biggest names in social media in the mid-2010s being Facebook, Instagram, Twitter and Snapchat. The massive influx of personal information that has become available online and stored in the cloud has put user privacy at the forefront of discussion regarding the database's ability to safely store such personal information. The extent to which users and social media platform administrators can access user profiles has become a new topic of ethical consideration, and the legality, awareness, and boundaries of subsequent privacy violations are critical concerns in advance of the technological age.
Social media began in the form of generalized online communities. These online communities formed on websites like Geocities.com in 1994, Theglobe.com in 1995, and Tripod.com in 1995. Many of these early communities focused on social interaction by bringing people together through the use of chat rooms. The chat rooms encouraged users to share personal information, ideas, or even personal web pages. Later the social networking community Classmates took a different approach by simply having people link to each other by using their personal email addresses. By the late 1990s, social networking websites began to develop more advanced features to help users find and manage friends. These newer generation of social networking websites began to flourish with the emergence of SixDegrees.com in 1997, Makeoutclub in 2000, Hub Culture in 2002, and Friendster in 2002. However, the first profitable mass social networking website was the South Korean service, Cyworld. Cyworld initially launched as a blog-based website in 1999 and social networking features were added to the website in 2001. Other social networking websites emerged like Myspace in 2002, LinkedIn in 2003, and Bebo in 2005. In 2009, the social networking website Facebook became the largest social networking website in the world. Active users of Facebook increased from just a million in 2004 to over 750 million by the year 2011. Making internet-based social networking both a cultural and financial phenomenon.
Infodemiology was defined by Gunther Eysenbach in the early 2000s as information epidemiology. It is an area of science research focused on scanning the internet for user-contributed health-related content, with the ultimate goal of improving public health. It is also defined as the science of mitigating public health problems resulting from an infodemic.
Social media mining is the process of obtaining big data from user-generated content on social media sites and mobile apps in order to extract actionable patterns, form conclusions about users, and act upon the information, often for the purpose of advertising to users or conducting research. The term is an analogy to the resource extraction process of mining for rare minerals. Resource extraction mining requires mining companies to shift through vast quantities of raw ore to find the precious minerals; likewise, social media mining requires human data analysts and automated software programs to shift through massive amounts of raw social media data in order to discern patterns and trends relating to social media usage, online behaviours, sharing of content, connections between individuals, online buying behaviour, and more. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as these organizations can use these patterns and trends to design their strategies or introduce new programs, new products, processes or services.
Thomas J. Coates is the Director of the multi-campus University of California Global Health Institute, a UC-wide initiative established to improve health and reduce the burden of disease throughout the world. He is Professor Emeritus at the UCLA David Geffen School of Medicine and Founding Director of the UCLA Center for World Health, a joint initiative of the David Geffen School of Medicine at UCLA and UCLA Health, He has conducted extensive research in the realm of HIV and is the Michael and Sue Steinberg Endowed Professor of Global AIDS Research within the Division of Infectious Diseases at UCLA and Distinguished Professor of Medicine. Health-related behavior is of particular interest to Coates. Throughout his career as a health expert, his theory-based research has been focused on interventions aimed at reducing risks and threats to health
Sean D. Young is an American social and behavioral psychologist. He is a medical school and Computer and Information Sciences professor with the University of California, Irvine (UCI). He serves as the executive director of the University of California, Institute for Prediction Technology (UCIPT) and the UCLA Center for Digital Behavior (CDB).
Data philanthropy describes a form of collaboration in which private sector companies share data for public benefit. There are multiple uses of data philanthropy being explored from humanitarian, corporate, human rights, and academic use. Since introducing the term in 2011, the United Nations Global Pulse has advocated for a global "data philanthropy movement".
A social bot, also described as a social AI or social algorithm, is a software agent that communicates autonomously on social media. The messages it distributes can be simple and operate in groups and various configurations with partial human control (hybrid) via algorithm. Social bots can also use artificial intelligence and machine learning to express messages in more natural human dialogue.
Black Swan Data is a London-based technology and data science company that produces a social prediction SaaS platform called Trendscope. Trendscope uses predictive data science and proprietary Natural Language Processing to analyze Social data conversations that help businesses identify potential trends and customer behaviors. Its notable clients include PepsiCo, Unilever, McDonald's, Danone, Disney and numerous others. In 2016, the company raised a total of £9.2 million in two separate funding rounds led by investors like Mitsui, Albion Ventures, and The Blackstone Group. The company is headquartered in London and has offices in New York, Budapest, Szeged, Cape Town and Exeter.
Artificial Intelligence for Digital Response (AIDR) is a free and open source platform to filter and classify social media messages related to emergencies, disasters, and humanitarian crises. It has been developed by the Qatar Computing Research Institute and awarded the Grand Prize for the 2015 Open Source Software World Challenge.
Participatory surveillance is community-based monitoring of other individuals. This term can be applied to both digital media studies and ecological field studies. In the realm of media studies, it refers to how users surveil each other using the internet. Either through the use of social media, search engines, and other web-based methods of tracking, an individual has the power to find information both freely or non freely given about the individual being searched. Issues of privacy emerge within this sphere of participatory surveillance, predominantly focused on how much information is available on the web that an individual does not consent to. More so, disease outbreak researchers can study social-media based patterns to decrease the time it takes to detect an outbreak, an emerging field of study called infodemiology. Within the realm of ecological fieldwork, participatory surveillance is used as an overarching term for the method in which indigenous and rural communities are used to gain greater accessibility to causes of disease outbreak. By using these communities, disease outbreak can be spotted earlier than through traditional means or healthcare institutions.
Caitlin M. Rivers is an American epidemiologist who as Senior Scholar at the Johns Hopkins Center for Health Security and assistant professor at the Johns Hopkins Bloomberg School of Public Health, specializing on improving epidemic preparedness. Rivers is currently working on the American response to the COVID-19 pandemic with a focus on the incorporation of infectious disease modeling and forecasting into public health decision making.