Tampere University of Technology

TUTCRIS Research Portal

Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Standard

Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media. / Salonen, Jaakko; Huhtamäki, Jukka; Nykänen, Ossi.

17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland. ACM, 2013. p. 131-138 (MindTrek Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Salonen, J, Huhtamäki, J & Nykänen, O 2013, Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media. in 17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland. MindTrek Conference, ACM, pp. 131-138. https://doi.org/10.1145/2523429.2523481

APA

Salonen, J., Huhtamäki, J., & Nykänen, O. (2013). Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media. In 17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland (pp. 131-138). (MindTrek Conference). ACM. https://doi.org/10.1145/2523429.2523481

Vancouver

Salonen J, Huhtamäki J, Nykänen O. Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media. In 17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland. ACM. 2013. p. 131-138. (MindTrek Conference). https://doi.org/10.1145/2523429.2523481

Author

Salonen, Jaakko ; Huhtamäki, Jukka ; Nykänen, Ossi. / Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media. 17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland. ACM, 2013. pp. 131-138 (MindTrek Conference).

Bibtex - Download

@inproceedings{9ae35f58a3c14cc293a9f1019f0a8831,
title = "Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media",
abstract = "Diverse data about various phenomena are implicitly available in the modern web. In particular websites categorized as social media provide rich and heterogeneous data about various entities such as people, corporations, brands as well as their properties and relationships. An analyst who seeks to leverage this diverse data is faced with the challenge of integrating and making sense of a set of heterogeneous data sources. In this paper, we provide an introduction and a problem statement for heterogeneous web data analytics. To further highlight and discuss practical challenges, we introduce a case study of Finnish growth companies in social media. Instead of a purely data-driven approach, the presented approach is rooted in the idea that an analyst can actively participate in the data collection and integration process, while the process can still retain repeatability and transparency. The key contribution of this paper is the statement of the challenges related to heterogeneous web data analytics.",
author = "Jaakko Salonen and Jukka Huhtam{\"a}ki and Ossi Nyk{\"a}nen",
note = "Contribution: organisation=mat,FACT1=1<br/>Portfolio EDEND: 2013-12-29<br/>Publisher name: ACM",
year = "2013",
doi = "10.1145/2523429.2523481",
language = "English",
isbn = "978-1-4503-1992-8",
series = "MindTrek Conference",
publisher = "ACM",
pages = "131--138",
booktitle = "17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Challenges in Heterogeneous Web Data Analytics - Case Finnish Growth Companies in Social Media

AU - Salonen, Jaakko

AU - Huhtamäki, Jukka

AU - Nykänen, Ossi

N1 - Contribution: organisation=mat,FACT1=1<br/>Portfolio EDEND: 2013-12-29<br/>Publisher name: ACM

PY - 2013

Y1 - 2013

N2 - Diverse data about various phenomena are implicitly available in the modern web. In particular websites categorized as social media provide rich and heterogeneous data about various entities such as people, corporations, brands as well as their properties and relationships. An analyst who seeks to leverage this diverse data is faced with the challenge of integrating and making sense of a set of heterogeneous data sources. In this paper, we provide an introduction and a problem statement for heterogeneous web data analytics. To further highlight and discuss practical challenges, we introduce a case study of Finnish growth companies in social media. Instead of a purely data-driven approach, the presented approach is rooted in the idea that an analyst can actively participate in the data collection and integration process, while the process can still retain repeatability and transparency. The key contribution of this paper is the statement of the challenges related to heterogeneous web data analytics.

AB - Diverse data about various phenomena are implicitly available in the modern web. In particular websites categorized as social media provide rich and heterogeneous data about various entities such as people, corporations, brands as well as their properties and relationships. An analyst who seeks to leverage this diverse data is faced with the challenge of integrating and making sense of a set of heterogeneous data sources. In this paper, we provide an introduction and a problem statement for heterogeneous web data analytics. To further highlight and discuss practical challenges, we introduce a case study of Finnish growth companies in social media. Instead of a purely data-driven approach, the presented approach is rooted in the idea that an analyst can actively participate in the data collection and integration process, while the process can still retain repeatability and transparency. The key contribution of this paper is the statement of the challenges related to heterogeneous web data analytics.

U2 - 10.1145/2523429.2523481

DO - 10.1145/2523429.2523481

M3 - Conference contribution

SN - 978-1-4503-1992-8

T3 - MindTrek Conference

SP - 131

EP - 138

BT - 17th International Academic MindTrek Conference, October 1-4, 2013, Tampere, Finland

PB - ACM

ER -