The Experts below are selected from a list of 335793 Experts worldwide ranked by ideXlab platform

Ling Li - One of the best experts on this subject based on the ideXlab platform.

  • Social media Competitive Analysis and text mining: A case study in the pizza industry
    International Journal of Information Management, 2013
    Co-Authors: Wu He, Shenghua Zha, Ling Li
    Abstract:

    Social media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase Competitive advantage and effectively assess the Competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media Competitive Analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media Competitive Analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media Competitive Analysis strategy.

Wu He - One of the best experts on this subject based on the ideXlab platform.

  • Social media Competitive Analysis and text mining: A case study in the pizza industry
    International Journal of Information Management, 2013
    Co-Authors: Wu He, Shenghua Zha, Ling Li
    Abstract:

    Social media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase Competitive advantage and effectively assess the Competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media Competitive Analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media Competitive Analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media Competitive Analysis strategy.

Moshe Tennenholtz - One of the best experts on this subject based on the ideXlab platform.

  • Rational Competitive Analysis
    arXiv: Artificial Intelligence, 2001
    Co-Authors: Moshe Tennenholtz
    Abstract:

    Much work in computer science has adopted Competitive Analysis as a tool for decision making under uncertainty. In this work we extend Competitive Analysis to the context of multi-agent systems. Unlike classical Competitive Analysis where the behavior of an agent's environment is taken to be arbitrary, we consider the case where an agent's environment consists of other agents. These agents will usually obey some (minimal) rationality constraints. This leads to the definition of rational Competitive Analysis. We introduce the concept of rational Competitive Analysis, and initiate the study of Competitive Analysis for multi-agent systems. We also discuss the application of rational Competitive Analysis to the context of bidding games, as well as to the classical one-way trading problem.

  • IJCAI - Rational Competitive Analysis
    2001
    Co-Authors: Moshe Tennenholtz
    Abstract:

    Much work in computer science has adopted Competitive Analysis as a tool for decision making under uncertainty. In this work we extend Competitive Analysis to the context of multi-agent systems. Unlike classical Competitive Analysis where the behavior of an agent's environment is taken to be arbitrary, we consider the case where an agent's environment consists of other agents. These agents will usually obey some (minimal) rationality constraints. This leads to the definition of rational Competitive Analysis. We introduce the concept of rational Competitive Analysis, and initiate the study of Competitive Analysis for multi-agent systems. We also discuss the application of rational Competitive Analysis to the context of bidding games, as well as to the classical oneway trading problem.

Shenghua Zha - One of the best experts on this subject based on the ideXlab platform.

  • Social media Competitive Analysis and text mining: A case study in the pizza industry
    International Journal of Information Management, 2013
    Co-Authors: Wu He, Shenghua Zha, Ling Li
    Abstract:

    Social media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase Competitive advantage and effectively assess the Competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media Competitive Analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media Competitive Analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media Competitive Analysis strategy.

Sabah Al Binali - One of the best experts on this subject based on the ideXlab platform.

  • The Competitive Analysis of Risk Taking with Applications to Online Trading
    2011
    Co-Authors: Sabah Al Binali
    Abstract:

    Competitive Analysis is concerned with minimizing a relative measure of performance When applied to nancial trading strategies Competitive Analysis leads to the development of strategies with minimum relative performance risk This approach is too in exible Many investors are interested in managing their risk they may be willing to increase their risk for some form of reward They may also have some forecast of the future In this paper we extend Competitive Analysis to provide a framework in which investors can develop optimal trading strategies based on their risk tolerance and forecast We rst de ne notions of risk and reward that are smooth extensions of classical Competitive Analysis We then illustrate our ideas using the ski rental problem and analyze a nancial game using the risk reward framework

  • A Risk‐Reward Framework for the Competitive Analysis of Financial Games
    Algorithmica, 1999
    Co-Authors: Sabah Al Binali
    Abstract:

    Competitive Analysis is concerned with minimizing a relative measure of performance. When applied to financial trading strategies, Competitive Analysis leads to the development of strategies with minimum relative performance risk. This approach is too inflexible. Many investors are interested in managing their risk: they may be willing to increase their risk for some form of reward. They may also have some forecast of the future. In this paper we extend Competitive Analysis to provide a framework in which investors can develop optimal trading strategies based on their risk tolerance and forecast. We first define notions of risk and reward that are natural extensions of classical Competitive Analysis and then illustrate our ideas using the ski-rental problem. Finally, we analyze a financial game using the risk—reward framework, and, in particular, derive an optimal risk-tolerant algorithm.

  • FOCS - The Competitive Analysis of risk taking with applications to online trading
    Proceedings 38th Annual Symposium on Foundations of Computer Science, 1
    Co-Authors: Sabah Al Binali
    Abstract:

    Competitive Analysis is concerned with minimizing a relative measure of performance. When applied to financial trading strategies, Competitive Analysis leads to the development of strategies with minimum relative performance risk. This approach is too inflexible. Many investors are interested in managing their risk: they may be willing to increase their risk for some form of reward. They may also have some forecast of the future. We extend Competitive Analysis to provide a framework in which investors can develop optimal trading strategies based on their risk tolerance and forecast. We first define notions of risk and reward that are smooth extensions of classical Competitive Analysis. We then illustrate our ideas using the ski-rental problem. Finally, we analyze a financial game, the unidirectional conversion problem. In particular, we present an optimal risk-tolerant algorithm for the forecast that prices will reach a certain level at some point during the game, and give numerical results of the investor's reward for making such a forecast.