Bar-Ilan University

About: Bar-Ilan University is a education organization based out in Ramat Gan, Israel. It is known for research contribution in the topics: Population & Poison control. The organization has 12835 authors who have published 34964 publications receiving 995648 citations. The organization is also known as: Bar Ilan University & BIU.

Debunking in a World of Tribes

Abstract: Social media aggregate people around common interests eliciting collective framing of narratives and worldviews. However, in such a disintermediated environment misinformation is pervasive and attempts to debunk are often undertaken to contrast this trend. In this work, we examine the effectiveness of debunking on Facebook through a quantitative analysis of 54 million users over a time span of five years (Jan 2010, Dec 2014). In particular, we compare how users usually consuming proven (scientific) and unsubstantiated (conspiracy-like) information on Facebook US interact with specific debunking posts. Our findings confirm the existence of echo chambers where users interact primarily with either conspiracy-like or scientific pages. However, both groups interact similarly with the information within their echo chamber. Then, we measure how users from both echo chambers interacted with 50,220 debunking posts accounting for both users consumption patterns and the sentiment expressed in their comments. Sentiment analysis reveals a dominant negativity in the comments to debunking posts. Furthermore, such posts remain mainly confined to the scientific echo chamber. Only few conspiracy users engage with corrections and their liking and commenting rates on conspiracy posts increases after the interaction.

Perceived Organizational Reputation and Organizational Performance: An Empirical Investigation of Industrial Enterprises

Abstract: This study analyzes the complex set of relationships among perceived organizational reputation, firm's quality of products/services, customers' satisfaction and multiple performance measures. A path analysis shows that reputation is influenced by customers' satisfaction, which is a mediator in the relationship between the firm's quality of products/services and reputation. Reputation is associated with the firm's growth and accumulation of customers' orders, but is not directly associated with market share, profitability and financial strength. Market share influences a firm's profitability and is a function of the firm's growth and accumulation of customers' orders, but it has no influence on the firm's financial strength.

Rey auditory-verbal learning test: Structure analysis

Abstract: One of the major advantages of the Rey Auditory-Verbal Learning Test (AVLT) is its multiple measures of learning and memory. This study evaluated empirically whether the different scores are, in fact, not merely different expressions of a single factor, but, rather, measures of different memory domains. The Rey AVLT was administered to 146 normal subjects. Factor analyses produced one, two, or three factors depending on the combination of scores included in the analysis and on the criteria used to determine the number of factors. The basic factors identified were acquisition and retention. The latter can be subdivided further into storage and retrieval, thus yielding a total of three factors.

Machine learning in acoustics: Theory and applications

Abstract: Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transformative potential of machine learning (ML), including deep learning, in the field of acoustics. ML is a broad family of techniques, which are often based in statistics, for automatically detecting and utilizing patterns in data. Relative to conventional acoustics and signal processing, ML is data-driven. Given sufficient training data, ML can discover complex relationships between features and desired labels or actions, or between features themselves. With large volumes of training data, ML can discover models describing complex acoustic phenomena such as human speech and reverberation. ML in acoustics is rapidly developing with compelling results and significant future promise. We first introduce ML, then highlight ML developments in four acoustics research areas: source localization in speech processing, source localization in ocean acoustics, bioacoustics, and environmental sounds in everyday scenes.