This week's guest, Phil Rosenzweig joined EconTalk host Russ Roberts to talk about his new book, Left Brain, Right Stuff. We'd like to know what you took away from this week's recorded conversation, and hopefully spark some more here online....
Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.
Nature.com Carrot or stick in motor learning Nature.com Carrot or stick: the manner by which reward and punishment affects motor learning is a long-standing question in education, sports, therapy and beyond.
Dan Gilbert presents research and data from his exploration of happiness -- sharing some surprising tests and experiments that you can also try on yourself. Watch through to the end for a sparkling Q&A with some familiar TED faces.
In the United States, social media sites—such as Facebook, Twitter, and YouTube—are currently being used by two out of three people (1), and search engines are used daily (2). Monitoring what users share or search for in social media and on the Web has led to greater insights into what people care about or pay attention to at any moment in time. Furthermore, it is also helping segments of the world population to be informed, to organize, and to react rapidly. However, social media and search results can be readily manipulated, which is something that has been underappreciated by the press and the general public.
In times of political elections, the stakes are high, and advocates may try to support their cause by active manipulation of social media. For example, altering the number of followers can affect a viewer's conclusion about candidate popularity. Recently, it was noted that the number of followers for a presidential candidate in the United States surged by over 110 thousand within one single day, and analysis showed that most of these followers are unlikely to be real people (3).
Social Scientists traditionally regard people's beliefs about the future to be exogenous to their desires and wishes. It's one thing to want something to happen, but it doesn't suppose to affect our beliefs that it will. My grandfather's German passport which I found among my dad's documents (see photo) shows how beliefs can be intermingled with wishes. Hugo Winter, a Jewish businessman from Koenigsberg, escaped Nazi Germany in 1934 to Palestine, leaving behind a flourishing business, a huge villa, and many friends and relatives. He never wanted to replace his fancy lifestyle in Germany
Philosophers at the Ruhr-Universität Bochum have put forward a new model that explains how humans recognise the emotions of others. According to their theory, humans are capable of perceiving feelings directly via pattern recognition.
It is generally assumed that the way people assess the relationship between a cause and an outcome is closely related to the actual evidence existing about the co-occurrence of these events. However, people’s estimations are often biased, and this usually translates into illusions of causality. Some have suggested that such illusions could be the result of previous knowledge-based expectations. In the present research we explored the role that previous knowledge has in the development of illusions of causality. We propose that previous knowledge influences the assessment of causality by influencing the decisions about responding or not (i.e., presence or absence of the potential cause), which biases the information people are exposed to, and this in turn produces illusions congruent with such biased information. In a non-contingent situation in which participants decided whether the potential cause was present or absent (Experiment 1), the influence of expectations on participants’ judgments was mediated by the probability of occurrence of the potential cause (determined by participants’ responses). However, in an identical situation, except that the participants were not allowed to decide the occurrence of the potential cause, only the probability of the cause was significant, not the expectations or the interaction. Together, these results support our hypothesis that knowledge-based expectations affect the development of causal illusions by the mediation of behavior, which biases the information received.
Adrian Jaeggi, University of California, Santa Barbara and Ben Trumble, University of California, Santa Barbara Much of human behavior is influenced by hormones. There’s cortisol, involved in our stress response and energy balance.
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