Paul F. Lazarsfeld

Bio: Paul F. Lazarsfeld is an academic researcher from Columbia University. The author has contributed to research in topics: Social research & Public opinion. The author has an hindex of 49, co-authored 153 publications receiving 20646 citations. Previous affiliations of Paul F. Lazarsfeld include Rockefeller Foundation & Braunschweig University of Technology.

The People's Choice: How the Voter Makes Up His Mind in a Presidential Campaign

Abstract: Die von Paul F. Lazarsfeld, Bernard Berelson und Hazel Gaudet 1944 veroffentlichte Studie The people’s choice untersucht den Prasidentschaft swahlkampf in den USA 1940. Analysiert wird: „How the voter makes up his mind in a presidential campaign”. Die Entstehung individueller Wahlentscheidungen und der Einfluss von Informationen verschiedener Quellen, u. a. der Medien wurden mittels eines fur die Zeit revolutionaren Paneldesigns untersucht. Die Studie begrundet einen Meilenstein in der kommunikationswissenschaftlichen Forschung, da sie den Grundstein fur einen Paradigmenwechsel legt, namlich die Abkehr von der Annahme des Publikums als Masse, die den Einflussen der Massenmedien ausgeliefert ist, hin zu den „limited effects“ der Medien. Ausschlaggebend fur diesen Paradigmenwechsel waren drei in The people’s choice vorgestellte Konzepte, die auch heute noch in der Kommunikationswissenschaft diskutiert werden: Die These der selektiven Zuwendung des Publikums zu Medieninhalten, das Konzept der Meinungsfuhrer und die These vom Zweistufenfluss der Kommunikation. In diesem Beitrag werden der Inhalt des Werkes sowie die Kritik daran mit Fokus auf diese drei Konzepte vorgestellt.

The people's choice.

Abstract: В своей классической работе «Выбор народа» группа авторов под руководством Пола Лазарсфельда впервые комплексно исследует влияние масс медиа на электоральное поведение на примере президентской кампании Рузвельта-Уилки 1940 года. На протяжении семи месяцев авторы опрашивают около 3000 респондентов и приходят к выводу, что мнение большинства людей зависит не напрямую от СМИ, а от других членов их первичных групп, которые и являются активными потребителями медиа-продукции. Этих людей авторы назвали прочно вошедшим в научный обиход термином «лидеры мнения».

Birds of a Feather: Homophily in Social Networks

Abstract: Similarity breeds connection. This principle—the homophily principle—structures network ties of every type, including marriage, friendship, work, advice, support, information transfer, exchange, comembership, and other types of relationship. The result is that people's personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics. Homophily limits people's social worlds in a way that has powerful implications for the information they receive, the attitudes they form, and the interactions they experience. Homophily in race and ethnicity creates the strongest divides in our personal environments, with age, religion, education, occupation, and gender following in roughly that order. Geographic propinquity, families, organizations, and isomorphic positions in social systems all create contexts in which homophilous relations form. Ties between nonsimilar individuals also dissolve at a higher rate, which sets the stage for the formation of niches (localize...

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Abstract: From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty—and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition—in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Estimating Nonresponse Bias in Mail Surveys

Abstract: Valid predictions for the direction of nonresponse bias were obtained from subjective estimates and extrapolations in an analysis of mail survey data from published studies For estimates of the magnitude of bias, the use of extrapolations led to substantial improvements over a strategy of not using extrapolations

Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication

Abstract: Background Little is known about the general population prevalence or severity of DSM-IV mental disorders. Objective To estimate 12-month prevalence, severity, and comorbidity of DSM-IV anxiety, mood, impulse control, and substance disorders in the recently completed US National Comorbidity Survey Replication. Design and Setting Nationally representative face-to-face household survey conducted between February 2001 and April 2003 using a fully structured diagnostic interview, the World Health Organization World Mental Health Survey Initiative version of the Composite International Diagnostic Interview. Participants Nine thousand two hundred eighty-two English-speaking respondents 18 years and older. Main Outcome Measures Twelve-month DSM-IV disorders. Results Twelve-month prevalence estimates were anxiety, 18.1%; mood, 9.5%; impulse control, 8.9%; substance, 3.8%; and any disorder, 26.2%. Of 12-month cases, 22.3% were classified as serious; 37.3%, moderate; and 40.4%, mild. Fifty-five percent carried only a single diagnosis; 22%, 2 diagnoses; and 23%, 3 or more diagnoses. Latent class analysis detected 7 multivariate disorder classes, including 3 highly comorbid classes representing 7% of the population. Conclusion Although mental disorders are widespread, serious cases are concentrated among a relatively small proportion of cases with high comorbidity.

Telling more than we can know: Verbal reports on mental processes.

Abstract: Evidence is reviewed which suggests that there may be little or no direct introspective access to higher order cognitive processes. Subjects are sometimes (a) unaware of the existence of a stimulus that importantly influenced a response, (b) unaware of the existence of the response, and (c) unaware that the stimulus has affected the response. It is proposed that when people attempt to report on their cognitive processes, that is, on the processes mediating the effects of a stimulus on a response, they do not do so on the basis of any true introspection. Instead, their reports are based on a priori, implicit causal theories, or judgments about the extent to which a particular stimulus is a plausible cause of a given response. This suggests that though people may not be able to observe directly their cognitive processes, they will sometimes be able to report accurately about them. Accurate reports will occur when influential stimuli are salient and are plausible causes of the responses they produce, and will not occur when stimuli are not salient or are not plausible causes.