The Experts below are selected from a list of 9735 Experts worldwide ranked by ideXlab platform
John S Lapinski - One of the best experts on this subject based on the ideXlab platform.
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Targeted Advertising and voter turnout an experimental study of the 2000 presidential election
The Journal of Politics, 2004Co-Authors: Joshua D Clinton, John S LapinskiAbstract:Scholars disagree whether negative Advertising demobilizes or stimulates the electorate. We use an experiment with over 10,200 eligible voters to evaluate the two leading hypotheses of negative political Advertising. We extend the analysis to examine whether Advertising differentially impacts the turnout of voter subpopulations depending on the advertisement’s message. In the short term, we find no evidence that exposure to negative advertisements decreases turnout and little that suggests it increases turnout. Any effect appears to depend upon the message of the advertisement and the characteristics of the viewer. In the long term, we find little evidence that the information contained in the treatment groups’ advertisements is sufficient to systematically alter turnout. Political pollsters, media consultants, members of the press, and scholars hold various opinions on whether “negative” Advertising is destabilizing democracy in America. The idea that negative campaigns decrease voter turnout and increase voter apathy was advanced by academics and warmly received by the news media. While perhaps intuitive and certainly eye-catching, this idea has recently come under attack. In the late 1980s and throughout the 1990s, scholars focused their attention on showing how campaigns matter. This work represents a direct attack on the minimal effects hypothesis associated with the Columbia and Michigan schools of voting (Lazarsfeld, Berelson, and Gaudet 1948; Berelson, Lazarsfeld, and McPhee 1954; Campbell et al. 1960; Campbell 2000). Of particular interest is the question of whether political advertisements—especially negative advertisements—demobilize or stimulate voters. Interest in the relationship between campaigns and voting has persisted for over fifty years, but only recently have researchers argued that political Advertising has contributed heavily to the disappearance of voters. Although scholars have used many methods to test if negative advertisements increase or decrease turnout, much remains unsettled.
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Targeted Advertising and voter turnout an experimental study of the 2000 presidential election
2004Co-Authors: Joshua D Clinton, John S LapinskiAbstract:Scholars disagree whether negative Advertising demobilizes or stimulates the electorate. We use an experiment with over 10,200 eligible voters to evaluate the two leading hypotheses of negative political Advertising. We extend the analysis to examine whether Advertising differentially impacts the turnout of voter subpopulations depending on the advertisement's message. In the short term, we find no evidence that exposure to negative advertisements decreases turnout and little that suggests it increases turnout. Any effect appears to depend upon the message of the advertisement and the characteristics of the viewer. In the long term, we find little evidence that the information contained in the treatment groups' advertisements is sufficient to systematically alter turnout.
Joshua D Clinton - One of the best experts on this subject based on the ideXlab platform.
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Targeted Advertising and voter turnout an experimental study of the 2000 presidential election
The Journal of Politics, 2004Co-Authors: Joshua D Clinton, John S LapinskiAbstract:Scholars disagree whether negative Advertising demobilizes or stimulates the electorate. We use an experiment with over 10,200 eligible voters to evaluate the two leading hypotheses of negative political Advertising. We extend the analysis to examine whether Advertising differentially impacts the turnout of voter subpopulations depending on the advertisement’s message. In the short term, we find no evidence that exposure to negative advertisements decreases turnout and little that suggests it increases turnout. Any effect appears to depend upon the message of the advertisement and the characteristics of the viewer. In the long term, we find little evidence that the information contained in the treatment groups’ advertisements is sufficient to systematically alter turnout. Political pollsters, media consultants, members of the press, and scholars hold various opinions on whether “negative” Advertising is destabilizing democracy in America. The idea that negative campaigns decrease voter turnout and increase voter apathy was advanced by academics and warmly received by the news media. While perhaps intuitive and certainly eye-catching, this idea has recently come under attack. In the late 1980s and throughout the 1990s, scholars focused their attention on showing how campaigns matter. This work represents a direct attack on the minimal effects hypothesis associated with the Columbia and Michigan schools of voting (Lazarsfeld, Berelson, and Gaudet 1948; Berelson, Lazarsfeld, and McPhee 1954; Campbell et al. 1960; Campbell 2000). Of particular interest is the question of whether political advertisements—especially negative advertisements—demobilize or stimulate voters. Interest in the relationship between campaigns and voting has persisted for over fifty years, but only recently have researchers argued that political Advertising has contributed heavily to the disappearance of voters. Although scholars have used many methods to test if negative advertisements increase or decrease turnout, much remains unsettled.
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Targeted Advertising and voter turnout an experimental study of the 2000 presidential election
2004Co-Authors: Joshua D Clinton, John S LapinskiAbstract:Scholars disagree whether negative Advertising demobilizes or stimulates the electorate. We use an experiment with over 10,200 eligible voters to evaluate the two leading hypotheses of negative political Advertising. We extend the analysis to examine whether Advertising differentially impacts the turnout of voter subpopulations depending on the advertisement's message. In the short term, we find no evidence that exposure to negative advertisements decreases turnout and little that suggests it increases turnout. Any effect appears to depend upon the message of the advertisement and the characteristics of the viewer. In the long term, we find little evidence that the information contained in the treatment groups' advertisements is sufficient to systematically alter turnout.
Michael I Jordan - One of the best experts on this subject based on the ideXlab platform.
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the missing piece in complex analytics low latency scalable model management and serving with velox
arXiv: Databases, 2014Co-Authors: Daniel Crankshaw, Peter Bailis, Joseph E Gonzalez, Zhao Zhang, Michael J Franklin, Ali Ghodsi, Michael I JordanAbstract:To support complex data-intensive applications such as personalized recommendations, Targeted Advertising, and intelligent services, the data management community has focused heavily on the design of systems to support training complex models on large datasets. Unfortunately, the design of these systems largely ignores a critical component of the overall analytics process: the deployment and serving of models at scale. In this work, we present Velox, a new component of the Berkeley Data Analytics Stack. Velox is a data management system for facilitating the next steps in real-world, large-scale analytics pipelines: online model management, maintenance, and serving. Velox provides end-user applications and services with a low-latency, intuitive interface to models, transforming the raw statistical models currently trained using existing offline large-scale compute frameworks into full-blown, end-to-end data products capable of recommending products, targeting advertisements, and personalizing web content. To provide up-to-date results for these complex models, Velox also facilitates lightweight online model maintenance and selection (i.e., dynamic weighting). In this paper, we describe the challenges and architectural considerations required to achieve this functionality, including the abilities to span online and offline systems, to adaptively adjust model materialization strategies, and to exploit inherent statistical properties such as model error tolerance, all while operating at "Big Data" scale.
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the missing piece in complex analytics low latency scalable model management and serving with velox
Conference on Innovative Data Systems Research, 2014Co-Authors: Daniel Crankshaw, Peter Bailis, Joseph E Gonzalez, Zhao Zhang, Michael J Franklin, Ali Ghodsi, Michael I JordanAbstract:To enable complex data-intensive applications such as personalized recommendations, Targeted Advertising, and intelligent services, the data management community has focused heavily on the design of systems to train complex models on large datasets. Unfortunately, the design of these systems largely ignores a critical component of the overall analytics process: the serving and management of models at scale. In this work, we present Velox, a new component of the Berkeley Data Analytics Stack. Velox is a data management system for facilitating the next steps in real-world, large-scale analytics pipelines: online model management, maintenance, and serving. Velox provides end-user applications and services with a low-latency, intuitive interface to models, transforming the raw statistical models currently trained using existing offline large-scale compute frameworks into full-blown, end-to-end data products capable of targeting advertisements, recommending products, and personalizing web content. To provide up-to-date results for these complex models, Velox also facilitates lightweight online model maintenance and selection (i.e., dynamic weighting). In this paper, we describe the challenges and architectural considerations required to achieve this functionality, including the abilities to span online and offline systems, to adaptively adjust model materialization strategies, and to exploit inherent statistical properties such as model error tolerance, all while operating at “Big Data” scale.
Paul Francis - One of the best experts on this subject based on the ideXlab platform.
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auctions in do not track compliant internet Advertising
Computer and Communications Security, 2011Co-Authors: Alexey Reznichenko, Saikat Guha, Paul FrancisAbstract:Online tracking of users in support of behavioral Advertising is widespread. Several researchers have proposed non-tracking online Advertising systems that go well beyond the requirements of the Do-Not-Track initiative launched by the US Federal Trace Commission (FTC). The primary goal of these systems is to allow for behaviorally Targeted Advertising without revealing user behavior (clickstreams) or user profiles to the ad network. Although these designs purport to be practical solutions, none of them adequately consider the role of the ad auctions, which today are central to the operation of online Advertising systems. This paper looks at the problem of running auctions that leverage user profiles for ad ranking while keeping the user profile private. We define the problem, broadly explore the solution space, and discuss the pros and cons of these solutions. We analyze the performance of our solutions using data from Microsoft Bing Advertising auctions. We conclude that, while none of our auctions are ideal in all respects, they are adequate and practical solutions.
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privad practical privacy in online Advertising
Networked Systems Design and Implementation, 2011Co-Authors: Saikat Guha, Bin Cheng, Paul FrancisAbstract:Online Advertising is a major economic force in the Internet today, funding a wide variety of websites and services. Today's deployments, however, erode privacy and degrade performance as browsers wait for ad networks to deliver ads. This paper presents Privad, an online Advertising system designed to be faster and more private than existing systems while filling the practical market needs of Targeted Advertising: ads shown in web pages; targeting based on keywords, demographics, and interests; ranking based on auctions; view and click accounting; and defense against click-fraud. Privad occupies a point in the design space that strikes a balance between privacy and practical considerations. This paper presents the design of Privad, and analyzes the pros and cons of various design decisions. It provides an informal analysis of the privacy properties of Privad. Based on microbenchmarks and traces from a production Advertising platform, it shows that Privad scales to present-day needs while simultaneously improving users' browsing experience and lowering infrastructure costs for the ad network. Finally, it reports on our implementation of Privad and deployment of over two thousand clients.
Yanmin Zhu - One of the best experts on this subject based on the ideXlab platform.
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towards correlated queries on trading of private web browsing history
International Conference on Computer Communications, 2020Co-Authors: Hui Cai, Yuanyuan Yang, Yanmin ZhuAbstract:With the commoditization of private data, data trading in consideration of user privacy protection has become a fascinating research topic. The trading for private web browsing histories brings huge economic value to data consumers when leveraged by Targeted Advertising. In this paper, we study the trading of multiple correlated queries on private web browsing history data. We propose TERBE, which is a novel trading framework for correlaTed quEries based on pRivate web Browsing historiEs. TERBE first devises a modified matrix mechanism to perturb query answers. It then quantifies privacy loss under the relaxation of classical differential privacy and a newly devised mechanism with relaxed matrix sensitivity, and further compensates data owners for their diverse privacy losses in a satisfying manner. Through real-data based experiments, our analysis and evaluation results demonstrate that TERBE balances total error and privacy preferences well within acceptable running time, and also achieves all desired economic properties of budget balance, individual rationality, and truthfulness.
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towards privacy preserving data trading for web browsing history
International Workshop on Quality of Service, 2019Co-Authors: Hui Cai, Yuanyuan Yang, Yanmin ZhuAbstract:The trading of social media data has attracted wide research interests over years. Especially the trading for web browsing histories probably produces tremendous economic value for data consumers when being applied to Targeted Advertising. However, the disclosure of entire browsing histories, even in form of anonymous datasets poses a huge threat to user privacy. Although some existing solutions have investigated privacy-preserving outsourcing of social media data, unfortunately, they neglected the impact on the data consumer's utility. In this paper, we propose PEATSE, a new Privacy-prEserving dAta Trading framework for web browSing historiEs. It takes users' diverse privacy preferences and the utility of their web browsing histories into consideration. PEATSE perturbs users' detailed browsing times on released browsing records to protect user privacy, while balancing the privacy-utility tradeoff. Through real-data based experiments, our analysis and evaluation results demonstrate PEATSE indeed achieves user privacy protection, the data consumer's accuracy requirement, and truthfulness, individual rationality as well as budget balance.
