Convergence rates of Kernel Conjugate Gradient for random design regression

We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient algorithm, where regularization against overfitting is obtained by early stopping. This method is related to Kernel Partial Least Squares, a regression method that combines supervised dimensionality reduction with least squares projection. Following the setting introduced in earlier related literature, we study so-called "fast convergence rates" depending on the regularity of the target regression function (measured by a source condition in terms of the kernel integral operator) and on the effective dimensionality of the data mapped into the kernel space. We obtain upper bounds, essentially matching known minimax lower bounds, for the $\mathcal{L}^2$ (prediction) norm as well as for the stronger Hilbert norm, if the true regression function belongs to the reproducing kernel Hilbert space. If the latter assumption is not fulfilled, we obtain similar convergence rates for appropriate norms, provided additional unlabeled data are available

The Degrees of Freedom of Partial Least Squares Regression

The derivation of statistical properties for Partial Least Squares regression can be a challenging task. The reason is that the construction of latent components from the predictor variables also depends on the response variable. While this typically leads to good performance and interpretable models in practice, it makes the statistical analysis more involved. In this work, we study the intrinsic complexity of Partial Least Squares Regression. Our contribution is an unbiased estimate of its Degrees of Freedom. It is defined as the trace of the first derivative of the fitted values, seen as a function of the response. We establish two equivalent representations that rely on the close connection of Partial Least Squares to matrix decompositions and Krylov subspace techniques. We show that the Degrees of Freedom depend on the collinearity of the predictor variables: The lower the collinearity is, the higher the Degrees of Freedom are. In particular, they are typically higher than the naive approach that defines the Degrees of Freedom as the number of components. Further, we illustrate how the Degrees of Freedom approach can be used for the comparison of different regression methods. In the experimental section, we show that our Degrees of Freedom estimate in combination with information criteria is useful for model selection.Comment: to appear in the Journal of the American Statistical Associatio

The need for privacy versus the urge to reveal the self

Self-disclosure helps us build and maintain relationships, but we need support against the push to disclose too much, write Johanna Schäwel and Nicole Kräme

I Spy with my Little Sensor Eye - Effect of Data-Tracking and Convenience on the Intention to Use Smart Technology.

The increasing number of smart objects in private households leads to a profound invasion of privacy. Based on privacy calculus theory, we assume that many users accept tracking in exchange for full functioning and convenience. However, privacy calculus has not yet been tested in an area where privacy protection is a binary decision: to either use a product or not. Therefore, we examined the effect of convenience and tracking on the intention to use a smart device in a 2 x 2 between-subjects online experiment (N = 209). While convenience is a major factor for the willingness to deploy smart technology, users do not seem to care whether these devices track their personal data or not

Expanding social identity theory for research in media effects: two international studies and a theoretical model

"In this paper we propose that Tajfel’s (1979) social identity theory (SIT) and self-categorization theory (SCT, Turner, Brown & Tajfel, 1987) is a relevant and helpful theoretical groundwork to explain selective exposure to media content in general and to entertainment media in particular. It is hypothesized that gender and national identity have a significant effect on selective exposure to entertainment series when being salient. Two international quasi-experimental studies have been conducted, the first study in the U.S. and Germany (N = 419) and the second in Great Britain and Germany (N = 154). As expected, participants rated series that feature protagonists of their own sex higher with regard to entertainment and intention to watch than those that featured protagonists of the opposite sex. However, national identity did not have the effects expected. Participants from all three countries gave similar ratings to series produced in their home-country as those produced abroad. The use of SIT is discussed in terms of what processes of the theory are of particular importance to explain media related behavior and how to empirically apply the theory in media effects research to make it work. A two-process model of SIT in media effects research is suggested: the process of social comparison is amended with a much simpler process of searching for similarities."[author´s abstract]"Im vorliegenden Beitrag werden die Theorie der sozialen Identität (Tajfel, 1979) und die Theorie der sozialen Kategorisierung (Turner, Brown & Tajfel, 1979) als theoretische Grundlage zur Erklärung der Medienselektion vorgeschlagen. In zwei Quasi-Experimenten wurde die untersucht, ob die Geschlechtszugehörigkeit beeinfluss, ob Probanden lieber unterhaltende TV Serien mit Protagonisten des eigenen Geschlechts oder des anderen Geschlechts sehen. Des Weiteren wurde untersucht, ob die nationale Identität beeinflusst, ob Probanden lieber unterhaltende TV Serien im TV sehen, die im Heimatland oder im Ausland produziert wurden. Die erste Studie wurde in den Vereinigten Staaten (U.S.A.) und Deutschland durchgeführt (N = 419), die zweite Studien in dem Vereinigten Königreich (U.K.) und Deutschland (N = 154). Die Ergebnisse weisen darauf hin, dass Probanden Serien mit Protagonisten des eigenen Geschlechts bevorzugen. Die nationale Identität hatte jedoch nicht den gewünschten Effekt. Die Probanden aller drei Länder bewerteten ausländische Produktionen besser als die Serien aus ihrem Heimatland. In der Diskussion und als Ergebnis der zwei Studien wird ein Zweiprozess-Modell der Medienselektion vorgeschlagen, das einerseits Prozesse der sozialen Identität und andererseits Prozesse der Ähnlichkeit als Ursachen der Medienselektion definiert."[Autorenreferat

Is Personality Key? Persuasive Effects of Prior Attitudes and Personality in Political Microtargeting

Messages that are designed to match a recipient’s personality, as enabled by microtargeting, have been found to influence political reasoning and even voting intentions. We extended these findings by adding prior attitudes to a microtargeting setting. Specifically, we examined what role different microtargeting approaches play in political reasoning by conducting an online experiment with a 2 (extraverted vs. introverted communication) × 2 (attitude-congruent vs. attitude-incongruent statement) between-subject design (N = 368). In line with the assumptions of the theory of motivated reasoning, attitude position matching emerged as an effective microtargeting strategy, and attitude strength moderated the effect of attitude congruency on recipients’ evaluations of political ads. While extraverted messages had no direct effect, that was unrelated to attitude congruency, recipients’ level of extraversion moderated the effect of extraverted communication on their evaluation of an ad. Interestingly, the intention to vote was significantly higher when an attitude-incongruent statement was phrased in an introverted rather than an extraverted manner, suggesting that information that challenges prior attitudes might be more persuasive when it is delivered in a more temperate way. In sum, the study indicates that matching message with personality alone might not be the most effective microtargeting approach within democratic societies

ASAP : automatic semantics-aware analysis of network payloads

Automatic inspection of network payloads is a prerequisite for effective analysis of network communication. Security research has largely focused on network analysis using protocol specifications, for example for intrusion detection, fuzz testing and forensic analysis. The specification of a protocol alone, however, is often not sufficient for accurate analysis of communication, as it fails to reflect individual semantics of network applications. We propose a framework for semantics-aware analysis of network payloads which automaticylly extracts semantic components from recorded network traffic. Our method proceeds by mapping network payloads to a vector space and identifying semantic templates corresponding to base directions in the vector space. We demonstrate the efficacy of semantics-aware analysis in different security applications: automatic discovery of patterns in honeypot data, analysis of malware communication and network intrusion detection

ASAP: Automatic semantics-aware analysis of network payloads

Automatic inspection of network payloads is a prerequisite for effective analysis of network communication. Security research has largely focused on network analysis using protocol specifications, for example for intrusion detection, fuzz testing and forensic analysis. The specification of a protocol alone, however, is often not sufficient for accurate analysis of communication, as it fails to reflect individual semantics of network applications. We propose a framework for semantics-aware analysis of network payloads which automaticylly extracts semantic components from recorded network traffic. Our method proceeds by mapping network payloads to a vector space and identifying semantic templates corresponding to base directions in the vector space. We demonstrate the efficacy of semantics-aware analysis in different security applications: automatic discovery of patterns in honeypot data, analysis of malware communication and network intrusion detection

The Impact of Twitter Features on Credibility Ratings - An Explorative Examination Combining Psychological Measurements and Feature Based Selection Methods

In a post-truth age determined by Social Media channels providing large amounts of information of questionable credibility while at the same time people increasingly tend to rely on online information, the ability to detect whether content is believable is developing into an important challenge. Most of the work in that field suggested automated approaches to perform binary classification to determine information veracity. Recipients´ perspectives and multidimensional psychological credibility measurements have rarely been considered. To fill this gap and gain more insights into the impact of a tweet´s features on perceived credibility, we conducted a survey asking participants (N=2626) to rate the credibility of crises related tweets. The resulting 24.823 ratings were used for an explorative feature selection analysis revealing that mostly meta-related features like the number of followers of the author, the count of tweets produced and the ratio of tweet number and days since account creation affect credibility judgements

The Shorter the Better? Effects of Privacy Policy Length on Online Privacy Decision-Making

Privacy policies provide Internet users with the possibility to inform themselves about websites’ usage of their disclosed personal data. Strikingly, however, most people tend not to read privacy policies because they are long and cumbersome, indicating that people do not wish to expend much (cognitive) effort on reading such policies. The present study aimed to examine whether shorter privacy policies can be beneficial in informing users about a social networking site’s (SNS) privacy practices, and to investigate associations between variables relevant for privacy decision-making using one theory-based integrative model. In an online experiment, participants (N = 305) were asked to create a personal account on an SNS after being given the option to read the privacy policy. Privacy policy length and the SNS’s level of privacy were varied, creating a 2 (policy length) x 2 (level of privacy) between-subjects design. The results revealed that participants who saw short policies spent less time on reading but gained higher knowledge about the SNS’s privacy practices - due to the fact that they spent more reading time per word. Factual privacy policy knowledge was found to be an indicator for participants’ subjective privacy perception. The perception and evaluation of the specific SNS´s privacy level influenced the assessment of privacy costs and benefits. Particularly when benefits were perceived as high, self-disclosure was increased