The Experts below are selected from a list of 222 Experts worldwide ranked by ideXlab platform

Taha Yasseri - One of the best experts on this subject based on the ideXlab platform.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    Royal Society Open Science, 2018
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects and the emergence of Web 2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the 'wisdom of the crowd' has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often unmonitored environment of such projects may make them susceptible to low-quality content. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. Urban Dictionary also contains offensive content, but highly offensive content tends to receive lower scores through the dictionary's voting system. The low threshold to include new material in Urban Dictionary enables quick recording of new words and new meanings, but the resulting heterogeneous content can pose challenges in using Urban Dictionary as a source to study language innovation.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    arXiv: Computation and Language, 2017
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects. The emergence of Web~2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the "wisdom of the crowd" has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often un-monitored environment of such projects may make them susceptible to systematic malfunction and misbehavior. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. There is also a high presence of offensive content, but highly offensive content tends to receive lower scores through the voting system. Our study highlights that Urban Dictionary has a higher content heterogeneity than found in traditional dictionaries, which poses challenges in terms in processing but also offers opportunities to analyze and track language innovation.

Dong Nguyen - One of the best experts on this subject based on the ideXlab platform.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    Royal Society Open Science, 2018
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects and the emergence of Web 2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the 'wisdom of the crowd' has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often unmonitored environment of such projects may make them susceptible to low-quality content. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. Urban Dictionary also contains offensive content, but highly offensive content tends to receive lower scores through the dictionary's voting system. The low threshold to include new material in Urban Dictionary enables quick recording of new words and new meanings, but the resulting heterogeneous content can pose challenges in using Urban Dictionary as a source to study language innovation.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    arXiv: Computation and Language, 2017
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects. The emergence of Web~2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the "wisdom of the crowd" has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often un-monitored environment of such projects may make them susceptible to systematic malfunction and misbehavior. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. There is also a high presence of offensive content, but highly offensive content tends to receive lower scores through the voting system. Our study highlights that Urban Dictionary has a higher content heterogeneity than found in traditional dictionaries, which poses challenges in terms in processing but also offers opportunities to analyze and track language innovation.

Warren Bailey - One of the best experts on this subject based on the ideXlab platform.

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Journal of Finance, 2003
    Co-Authors: Warren Bailey, Connie X Mao, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while imposing greater demands on investment professionals

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Journal of Finance, 2003
    Co-Authors: Warren Bailey, Haitao Li, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while imposing greater demands on investment professionals. Copyright 2003 by the American Finance Association.

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Social Science Research Network, 2003
    Co-Authors: Warren Bailey, Connie X Mao, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while demanding more effort and struggle from investment professionals.

Rui Zhong - One of the best experts on this subject based on the ideXlab platform.

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Journal of Finance, 2003
    Co-Authors: Warren Bailey, Connie X Mao, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while imposing greater demands on investment professionals

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Journal of Finance, 2003
    Co-Authors: Warren Bailey, Haitao Li, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while imposing greater demands on investment professionals. Copyright 2003 by the American Finance Association.

  • regulation fair disclosure and earnings Information Market analyst and corporate responses
    Social Science Research Network, 2003
    Co-Authors: Warren Bailey, Connie X Mao, Rui Zhong
    Abstract:

    With the adoption of Regulation Fair Disclosure (Reg FD), Market behavior around earnings releases displays no significant change in return volatility (after controlling for decimalization of stock trading) but significant increases in trading volume due to difference in opinion. Analyst forecast dispersion increases, and increases in other measures of disagreement and difference of opinion suggest greater difficulty in forming forecasts beyond the current quarter. Corporations increase the quantity of voluntary disclosures, but only for current quarter earnings. Thus, Reg FD seems to increase the quantity of Information available to the public while demanding more effort and struggle from investment professionals.

Barbara Mcgillivray - One of the best experts on this subject based on the ideXlab platform.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    Royal Society Open Science, 2018
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects and the emergence of Web 2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the 'wisdom of the crowd' has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often unmonitored environment of such projects may make them susceptible to low-quality content. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. Urban Dictionary also contains offensive content, but highly offensive content tends to receive lower scores through the dictionary's voting system. The low threshold to include new material in Urban Dictionary enables quick recording of new words and new meanings, but the resulting heterogeneous content can pose challenges in using Urban Dictionary as a source to study language innovation.

  • emo love and god making sense of urban dictionary a crowd sourced online dictionary
    arXiv: Computation and Language, 2017
    Co-Authors: Dong Nguyen, Barbara Mcgillivray, Taha Yasseri
    Abstract:

    The Internet facilitates large-scale collaborative projects. The emergence of Web~2.0 platforms, where producers and consumers of content unify, has drastically changed the Information Market. On the one hand, the promise of the "wisdom of the crowd" has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based Information in many languages. On the other hand, the decentralized and often un-monitored environment of such projects may make them susceptible to systematic malfunction and misbehavior. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. There is also a high presence of offensive content, but highly offensive content tends to receive lower scores through the voting system. Our study highlights that Urban Dictionary has a higher content heterogeneity than found in traditional dictionaries, which poses challenges in terms in processing but also offers opportunities to analyze and track language innovation.