Purchase Intentions on Social Media as Predictors of Consumer Spending

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

Abstract

The paper addresses the problem of forecasting consumer expenditure from social media data. Previous research of the topic exploited the intuition that search engine traffic reflects purchase intentions and constructed predictive models of consumer behaviour from search query volumes. In contrast, we derive predictors from explicit expressions of purchase intentions found in social media posts. Two types of predictors created from these expressions are explored: those based on word embeddings and those based on topical word clusters. We introduce a new clustering method, which takes into account temporal co-occurrence of words, in addition to their semantic similarity, in order to create predictors relevant to the forecasting problem. The predictors are evaluated against baselines that use only macroeconomic variables, and against models trained on search traffic data. Conducting experiments with three different regression methods on Facebook and Twitter data, we find that both word embeddings and word clusters help to reduce forecasting errors in comparison to purely macroeconomic models. In most experimental settings, the error reduction is statistically significant, and is comparable to error reduction achieved with search traffic variables.
Original languageEnglish
Title of host publicationProceedings of the Fourteenth International AAAI Conference on Web and Social Media
PublisherAAAI
Number of pages12
Volume14
Publication statusAccepted/In press - 1 May 2020
Event14th International Conference on Web and Social Media - Atlanta, United States
Duration: 8 Jun 202011 Jun 2020
Conference number: 14
https://www.icwsm.org/2020/index.html

Publication series

NameProceedings of the International AAAI Conference on Web and Social Media
PublisherAAAI
Volume14
ISSN (Print)2162-3449
ISSN (Electronic)2334-0770

Conference

Conference14th International Conference on Web and Social Media
Abbreviated titleICSWM
CountryUnited States
CityAtlanta
Period8/06/2011/06/20
Internet address

Bibliographical note

Copyright 2020, Association for the Advancement of Artificial
Intelligence (www.aaai.org). All rights reserved.

Keywords

  • social media
  • Natural Language Processing
  • Macroeconomic forecasting

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  • Cite this

    Pekar, V. (Accepted/In press). Purchase Intentions on Social Media as Predictors of Consumer Spending. In Proceedings of the Fourteenth International AAAI Conference on Web and Social Media (Vol. 14). (Proceedings of the International AAAI Conference on Web and Social Media; Vol. 14). AAAI.