Decoding data analytics capabilities from topic modeling on press releases

Jeancarlo Bonilla, Bharadwaj Rao

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In their quest for data-driven insight, firms align their resources to produce information that is actionable. Moreover, the bundling and utilization of these valuable resources is what defines an organizational capability. Thus, in this paper we conceptualize a new type of capability - data analytics capabilities, DAC, as the ability to assemble, coordinate, mobilize, and deploy analytics-based resources with strategic purpose. Using text as data, we explore the use of probabilistic topic modeling on historical press releases, in an attempt to identify types of DAC from successful data analytics investments. Press and news releases frequently articulate a firm's resource allocation strategy, proving an opportunity to automatically classify these into topics that can suggest categorization of DAC. We explore 8-year historical press releases and apply Latent Dirichlet Allocation topic modeling to 273 press releases.

    Original languageEnglish (US)
    Title of host publicationPICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings
    PublisherPortland State University
    Pages1959-1968
    Number of pages10
    Volume2015-September
    ISBN (Print)9781890843328
    DOIs
    StatePublished - Sep 21 2015
    EventPortland International Center for Management of Engineering and Technology, PICMET 2015 - Portland, United States
    Duration: Aug 2 2015Aug 6 2015

    Other

    OtherPortland International Center for Management of Engineering and Technology, PICMET 2015
    CountryUnited States
    CityPortland
    Period8/2/158/6/15

    Fingerprint

    Resource allocation
    Decoding
    Press releases
    Modeling
    Resources

    ASJC Scopus subject areas

    • Engineering(all)
    • Strategy and Management

    Cite this

    Bonilla, J., & Rao, B. (2015). Decoding data analytics capabilities from topic modeling on press releases. In PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings (Vol. 2015-September, pp. 1959-1968). [7273249] Portland State University. https://doi.org/10.1109/PICMET.2015.7273249

    Decoding data analytics capabilities from topic modeling on press releases. / Bonilla, Jeancarlo; Rao, Bharadwaj.

    PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings. Vol. 2015-September Portland State University, 2015. p. 1959-1968 7273249.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Bonilla, J & Rao, B 2015, Decoding data analytics capabilities from topic modeling on press releases. in PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings. vol. 2015-September, 7273249, Portland State University, pp. 1959-1968, Portland International Center for Management of Engineering and Technology, PICMET 2015, Portland, United States, 8/2/15. https://doi.org/10.1109/PICMET.2015.7273249
    Bonilla J, Rao B. Decoding data analytics capabilities from topic modeling on press releases. In PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings. Vol. 2015-September. Portland State University. 2015. p. 1959-1968. 7273249 https://doi.org/10.1109/PICMET.2015.7273249
    Bonilla, Jeancarlo ; Rao, Bharadwaj. / Decoding data analytics capabilities from topic modeling on press releases. PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings. Vol. 2015-September Portland State University, 2015. pp. 1959-1968
    @inproceedings{a17f1f112b114f9cb01d50413a2dd3c0,
    title = "Decoding data analytics capabilities from topic modeling on press releases",
    abstract = "In their quest for data-driven insight, firms align their resources to produce information that is actionable. Moreover, the bundling and utilization of these valuable resources is what defines an organizational capability. Thus, in this paper we conceptualize a new type of capability - data analytics capabilities, DAC, as the ability to assemble, coordinate, mobilize, and deploy analytics-based resources with strategic purpose. Using text as data, we explore the use of probabilistic topic modeling on historical press releases, in an attempt to identify types of DAC from successful data analytics investments. Press and news releases frequently articulate a firm's resource allocation strategy, proving an opportunity to automatically classify these into topics that can suggest categorization of DAC. We explore 8-year historical press releases and apply Latent Dirichlet Allocation topic modeling to 273 press releases.",
    author = "Jeancarlo Bonilla and Bharadwaj Rao",
    year = "2015",
    month = "9",
    day = "21",
    doi = "10.1109/PICMET.2015.7273249",
    language = "English (US)",
    isbn = "9781890843328",
    volume = "2015-September",
    pages = "1959--1968",
    booktitle = "PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings",
    publisher = "Portland State University",

    }

    TY - GEN

    T1 - Decoding data analytics capabilities from topic modeling on press releases

    AU - Bonilla, Jeancarlo

    AU - Rao, Bharadwaj

    PY - 2015/9/21

    Y1 - 2015/9/21

    N2 - In their quest for data-driven insight, firms align their resources to produce information that is actionable. Moreover, the bundling and utilization of these valuable resources is what defines an organizational capability. Thus, in this paper we conceptualize a new type of capability - data analytics capabilities, DAC, as the ability to assemble, coordinate, mobilize, and deploy analytics-based resources with strategic purpose. Using text as data, we explore the use of probabilistic topic modeling on historical press releases, in an attempt to identify types of DAC from successful data analytics investments. Press and news releases frequently articulate a firm's resource allocation strategy, proving an opportunity to automatically classify these into topics that can suggest categorization of DAC. We explore 8-year historical press releases and apply Latent Dirichlet Allocation topic modeling to 273 press releases.

    AB - In their quest for data-driven insight, firms align their resources to produce information that is actionable. Moreover, the bundling and utilization of these valuable resources is what defines an organizational capability. Thus, in this paper we conceptualize a new type of capability - data analytics capabilities, DAC, as the ability to assemble, coordinate, mobilize, and deploy analytics-based resources with strategic purpose. Using text as data, we explore the use of probabilistic topic modeling on historical press releases, in an attempt to identify types of DAC from successful data analytics investments. Press and news releases frequently articulate a firm's resource allocation strategy, proving an opportunity to automatically classify these into topics that can suggest categorization of DAC. We explore 8-year historical press releases and apply Latent Dirichlet Allocation topic modeling to 273 press releases.

    UR - http://www.scopus.com/inward/record.url?scp=84955621444&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84955621444&partnerID=8YFLogxK

    U2 - 10.1109/PICMET.2015.7273249

    DO - 10.1109/PICMET.2015.7273249

    M3 - Conference contribution

    AN - SCOPUS:84955621444

    SN - 9781890843328

    VL - 2015-September

    SP - 1959

    EP - 1968

    BT - PICMET 2015 - Portland International Center for Management of Engineering and Technology: Management of the Technology Age, Proceedings

    PB - Portland State University

    ER -