Publikation:

Integrating Sentiment Analysis and Term Associations with Geo-Temporal Visualizations on Customer Feedback Streams

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2012

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Hao, Ming
Dayal, Umeshwar
Haug, Lars-Erik
Hsu, Mei-Chun

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http://nbn-resolving.de/urn:nbn:de:bsz:352-225981
DOI (zitierfähiger Link)
https://doi.org/10.1117/12.912202
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WONG, Pak Chung, ed. and others. Visualization and Data Analysis 2012. SPIE, 2012, pp. 82940H. SPIE Proceedings. 8294. Available under: doi: 10.1117/12.912202

Zusammenfassung

Twitter currently receives over 190 million tweets (small text-based Web posts) and manufacturing companies receive over 10 thousand web product surveys a day, in which people share their thoughts regarding a wide range of products and their features. A large number of tweets and customer surveys include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for determining customer sentiments. To explore high-volume customer feedback streams, we integrate three time series-based visual analysis techniques: (1) feature-based sentiment analysis that extracts, measures, and maps customer feedback; (2) a novel idea of term associations that identify attributes, verbs, and adjectives frequently occurring together; and (3) new pixel cell-based sentiment calendars, geo-temporal map visualizations and self-organizing maps to identify co-occurring and influential opinions. We have combined these techniques into a well-fitted solution for an effective analysis of large customer feedback streams such as for movie reviews (e.g., Kung-Fu Panda) or web surveys (buyers).

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004 Informatik

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IS&T/SPIE Electronic Imaging, Burlingame, California, USA
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ISO 690HAO, Ming, Christian ROHRDANTZ, Halldor JANETZKO, Daniel A. KEIM, Umeshwar DAYAL, Lars-Erik HAUG, Mei-Chun HSU, 2012. Integrating Sentiment Analysis and Term Associations with Geo-Temporal Visualizations on Customer Feedback Streams. IS&T/SPIE Electronic Imaging. Burlingame, California, USA. In: WONG, Pak Chung, ed. and others. Visualization and Data Analysis 2012. SPIE, 2012, pp. 82940H. SPIE Proceedings. 8294. Available under: doi: 10.1117/12.912202
BibTex
@inproceedings{Hao2012-06-19Integ-22598,
  year={2012},
  doi={10.1117/12.912202},
  title={Integrating Sentiment Analysis and Term Associations with Geo-Temporal Visualizations on Customer Feedback Streams},
  number={8294},
  publisher={SPIE},
  series={SPIE Proceedings},
  booktitle={Visualization and Data Analysis 2012},
  editor={Wong, Pak Chung},
  author={Hao, Ming and Rohrdantz, Christian and Janetzko, Halldor and Keim, Daniel A. and Dayal, Umeshwar and Haug, Lars-Erik and Hsu, Mei-Chun}
}
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