A long-standing debate is whether social influence improves the collective wisdom of a crowd or undermines it. This paper addresses question based on naïve learning setting in systems theory: our models individuals evolve their estimates an unknown truth according to weighted-average opinion dynamics. formal mathematization provided with rigorous theoretical analysis. We obtain various conditio...

There are many tracking methods been proposed, using different features and algorithms, but none of them can track object correctly all the time. In this paper, we explore the idea of combining a crowd of trackers, and propose a crowdsourcing tracking method. We model the problem under the Sequential Monte Carlo framework, where we treat different trackers outputs, the bounding boxes, as weak o...

TweetTrader.net is a stock microblogging forum that leverages the wisdom of crowds to aggregate the information contained in stock-related tweets. Based on insights from academic research on stock microblogs, the application integrates inputs from text classification, user voting and a proprietary Stock Game in order to extract the sentiment (i.e., the bullishness) of online investors with resp...

We study a novel mechanism design model in which agents arrive sequentially and each in turn chooses one action from a set of actions with unknown rewards. The information that becomes available affects the incentives of an agent to explore and generate new information. We characterize the optimal disclosure policy of a planner whose goal is to maximizes social welfare. One interpretation for o...

This essay, exploring the peer-to-peer collaborative atmosphere penetrating Wikivism, crowd-sourcing and open-source movement, identifies a new paradigm of public information as evolution toward Wiki-government. Citizen participants can collectively create public information via various platforms enabled by Web 2.0 technologies. Under the new participatory paradigm that a large number of indivi...

In this article, we present a comprehensive study aimed at computing semantic relatedness of word pairs. We analyze the performance of a large number of semantic relatedness measures proposed in the literature with respect to different experimental conditions, such as (i) the datasets employed, (ii) the language (English or German), (iii) the underlying knowledge source, and (iv) the evaluation...

We introduce the study of adversarial effects on wisdom of the crowd phenomena. In particular, we examine the ability of an adversary to influence a social network so that the majority of nodes are convinced by a falsehood, using its power to influence a certain fraction, μ < 0.5 of N experts. Can a bad restaurant make a majority of the overall network believe in the quality of that restaurant ...

The interest in the wisdom of crowds stems mainly from possibility combining independent forecasts experts hope that many expert minds are better than a few. Hence relevant subject study nowadays is Vox Expertorum rather Galton’s original Populi. Here we use Federal Reserve Bank Philadelphia’s Survey Professional Forecasters to analyze 15455 forecasting contests predict variety economic indicat...