Social Media Geoforensics:Implications For Marketers
Sy Banerjee*,
Associate Professor
School of Management
University of Michigan, Flint,
Fareena Sultan,
Professor
D’AmoreMcKim School of Business
Northeastern University, Boston, MA, USA
*Corresponding Author
May 31, 2016
Social Media Geoforensics:Implications For Marketers
Social media has become an increasingly important source of user-generated content and rising data availability. Social sharing is nowan important component of the consumer’s consumption experience in the mobile environment.In this paper, the authors examine how location-based data captured by mobile social networks can be used by marketers to understand and monitor social media content.By Social Media Geoforensics we mean the process of analyzing physical context-specific information from location-based social networks to design and utilize new social media metrics that can help marketers understand mobile consumer behavior.
This exploratory study examines the influence of location on the type of social media content generated by consumers. A consumer’s location has far more information than being a mere geographical marker, as shown by applications like Foursquare. Knowing a person is inside a particular restauranttweeting on a Friday evening can help marketers understand not only where the person is, but also what mood he may be in, what he is doing, and who else may be accompanying him.
Most studies on Location-based Mobile Social Networks (LBMSN) have computed tweet sentiment scores based on words in the tweet. In this study, we design a new way of classifying tweet contentinto four distinct categories. The uniqueness of this categorization is that it interprets the typology of the tweet based on the physical context of the tweet. Category one is the most “abstract” where the consumer is lost in thought, thinking about a topic that doesn’t relate to the environment he is in. Category two defines thoughts about the tweeter’s personal life, schedules, and relationships. Category three is about the geographical region, neighborhood, block around the person’s current location. Category four is the most “concrete” category, where consumers’ attention is on his or her immediate surroundings.The same tweet related to a sports team could belong to different category if the user was watching the game checked into a physical sports arena instead of watching it on TV in a sports bar.
We also propose two new metrics, Venue Variability and Inward-Outward Directedness as mobile markers that contribute to the building blocks of social media content. Venue variability is defined as the extent to which individuals check-in and tweet from multiple types of locations, (such as Food, Arts and Entertainment, Travel, Shopping, Nightlife), Inward-Outward directedness of the tweet indicates whether the content of the tweet is more about the individual’s personal life, or more about the immediate surrounding environment. Whereas Venue Variabilitycan be used to determine the user’s flexibility of information sharing and breadth of experiences across multiple categories, the Inward-Outwards metric can help understand the type of insights can be mined from those tweets. These metrics can help marketers better segment customers and understand inferences that can be drawn from mining tweet content (for example, mining tweets that contain more about surrounding venues can help assess the customer’s service experiences).
An empirical examinationis conducted in which we track consumers checking-in at restaurants, bars, museums, offices, residences, parks and other venues. We utilize the new categorization scheme and new metrics based on a sample of tweets and location information from 6 selectedregions in the US. These six regions were chosen for analysis because of the high volume of check-ins emanating from them on Foursquare.We propose that examinationsbased on such Geoforensics can lead to a better understanding of consumer behavior on social networks. It can also help marketers in such activities as better segmentation, targeting, promotion timing, and promotion design, as well as in improving service experiences through real-time insights.