Partner-marketing using geo-social media data for smarter commerce

Bao, Jie; Deshpande, Anant; McFaddin, Scott; Narayanaswami, Chandra

doi:10.1147/jrd.2014.2344514

Cited by 3 publications

(1 citation statement)

References 12 publications

(12 reference statements)

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“…This leads to assess correctly short period trends and consequently to adjust eventual advertisement campaigns, according to the advantages or drawbacks of the considered product. An innovative usage of social big data in this category is presented in [7],…”

Section: Fostering Of Commercials and Promotion Activitiesmentioning

confidence: 99%

A glimpse on big data analytics in the framework of marketing strategies

2017

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Mining and analyzing the valuable knowledge hidden behind the amount of data available in social media is becoming a fundamental prerequisite for any effective and successful strategic marketing campaign. Anyway, to the best of our knowledge, a systematic analysis and review of the very recent literature according to a marketing framework is still missing. In this work, we intend to provide, first and foremost, a clear understanding of the main concepts and issues regarding social big data, as well as their features and technologies. Secondly, we focus on marketing, describing an operative methodology to get useful insights from social big data. Then, we carry out a brief but accurate classification of recent use cases from the literature, according to the decision support and the competitive advantages obtained by enterprises whenever they exploit the analytics available from social big data sources. Finally, we outline some open issues and suggestions in order to encourage further research in the field

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Section: Fostering Of Commercials and Promotion Activitiesmentioning

confidence: 99%

A glimpse on big data analytics in the framework of marketing strategies

2017

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Geo-social media data analytic for user modeling and location-based services

et al. 2016

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More and more geo-tagged social media data is generated, nowadays, from the geo-tagged tweets, geo-tagged photos to check-ins. Analyzing this flourish data enables the possibility for us to discover users daily mobility patterns, profiles and preferences. As a result, based on the analyzed results, new types of location-based services emerge. In this article, we first introduce the recent advances in location-based user preferences modeling, which includes: 1) inferring users demographics, 2) identifying users novelty-seeking characteristics and 3) discovering users shopping impulsiveness. After that, we present a comprehensive summary on the state-of-arts of the location-based services, which take advantage of the geo-social media, including: 1) location-based recommendations, 2) location-based predication.

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