3,711 research outputs found

    VIP: Incorporating Human Cognitive Biases in a Probabilistic Model of Retweeting

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    Information spread in social media depends on a number of factors, including how the site displays information, how users navigate it to find items of interest, users' tastes, and the `virality' of information, i.e., its propensity to be adopted, or retweeted, upon exposure. Probabilistic models can learn users' tastes from the history of their item adoptions and recommend new items to users. However, current models ignore cognitive biases that are known to affect behavior. Specifically, people pay more attention to items at the top of a list than those in lower positions. As a consequence, items near the top of a user's social media stream have higher visibility, and are more likely to be seen and adopted, than those appearing below. Another bias is due to the item's fitness: some items have a high propensity to spread upon exposure regardless of the interests of adopting users. We propose a probabilistic model that incorporates human cognitive biases and personal relevance in the generative model of information spread. We use the model to predict how messages containing URLs spread on Twitter. Our work shows that models of user behavior that account for cognitive factors can better describe and predict user behavior in social media.Comment: SBP 201

    REITs and Idiosyncratic Risk

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    This study examines various determinants of idiosyncratic risk from the perspective of un-diversified REIT investors, managers holding options, other option holders, and arbitrageurs. Since real estate investment trusts (REITs) enjoy a unique organizational structure and tax status, the relevant determinants derived from the two-stage regression model are different from other industrial firms. Results suggest that efficiency, liquidity and earnings variability are the important determinants of idiosyncratic risk, whereas size and capital do not

    Stationarity and Co-Integration in Systems with Three National Real Estate Indices

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    This study examines the stochastic properties of the commercial real estate wealth indices for three countries (the U.S., Canada, and the U.K.) and for several property types (aggregate, office, retail, and industrial). Each of the indices is tested for a unit root and all series are found to be nonstationary. Furthermore, all indices also indicate the presence of both drift and trend. The results are strongest when the indices are tested in real estate and exchange rate-adjusted form. Application of Johansen's model indicates that the system for the three countries shows evidence of co-integration for the aggregate, retail, office, and industrial properties. Again, the evidence is the strongest when the indices are tested in real and exchange rate-adjusted form. Hence, it is conceivable that inflationary expectations may be the factor that provides the common linkage between commercial real estate across national boundaries.

    Characterization of copper resistant ciliates: Potential candidates for consortia of organisms used in bioremediation of wastewater

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    Metals are environmental pollutants of major concern due to their ecological, sanitary and even economic consequences. Both prokaryotes and eukaryotes inhabiting such environments carry cellular systems that maintain the metal homeostasis. The ciliate protists tolerate elevated concentrations of metals, which are accumulated, bound to metallothioneins (MTs) peculiar to these organisms. Copper is one of such contaminant found in the wastewater of local industries. The concentrations of copper which caused 50% reduction (LC50) in the cell population of Tetrahymena sp RT1, and two Euplotes spp. RE-1 and RE-2, isolated from the industrial waste, were found to be 60, 48 and 49 ppm, respectively, compared to those of the cultures without copper in the media. RT-1 showed significantly high tolerance to copper ions and could uptake 52.66% of the copper ions from the medium. The axenic culture of RT-1 could uptake 61.2% of copper from the medium compared to 68.41 and 59.16% by the ATCC culture of Tetrahymena thermophila and T. pyriformis, respectively. RT-1 tolerated about 500 μM copper in the medium without affecting its movement. This ciliate showed promise as a member of the consortium used for bioremediation of copper contaminated wastewater.Key words: Copper toxicity, metallothionein, growth curve of ciliates, metal uptake, bioremediation
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