MIS Distinguished Speaker Series

Temple University

Fox School of Business
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Mar 5 – Monideepa Tarafdar to present “Role of Social Media in Social Protest Cycles: A Sociomaterial Examination”

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Role of Social Media in Social Protest Cycles: A Sociomaterial Examination

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Monideepa Tarafdar

Charles J. Dockendorff Endowed Professor
Operations & Information Management
Isenberg School of Management
University of Massachusetts Amherst

Friday, Mar 5

10 – 11 am | Zoom

(send an email to ayabakan@temple.edu to get the Zoom link)

Abstact:

Contemporary social media fueled social protest is self-organized, rapidly dynamic, and de-centralized, constitutes vast populations, and is shaped by multiple and concurrent channels of information flows. Who can forget the powerful images of the many different social medial fueled protests, across the world, from 2018 through early 2021? Such protest activity is captured in the concept of ‘social protest cycles’, which are short periods of intense and contentious protest activity characterized by temporal dynamics, a large repertoire of protest action, confrontation and potential violence, and possible institutional action. They are the micro-foundations of long-term social movements. Drawing from the theoretical concept of sociomaterial assemblages, we conceptualize the social media enabled social protest cycle as an assemblage having social (e.g., people, elected leaders, police, judges etc.) and technical (social media applications, online petition applications etc.) components and analyze how it transforms through performative intra-actions. The empirical context is a social media enabled social protest cycle that emerged following a fatal rape incident in New Delhi, India. Through mixed-methods analysis of longitudinal netnographic data collected from simultaneous protest activity on Twitter, Facebook, YouTube, online blogs, and newspaper websites, we theorize three intra-actions – Consolidation, Expansion and Intensification – and explain how they transform the social protest cycle over time. The paper contributes to the IS literature that studies social media enabled social protest action.

Dec 4 – Wendy Duan to present “Does Social Media Accelerate Product Recalls? Evidence from the Pharmaceutical Industry”

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Does Social Media Accelerate Product Recalls? Evidence from the Pharmaceutical Industry

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Wenjing (Wendy) Duan

Associate Professor
Information Systems & Technology Management
School of Business
The George Washington University

Friday, Dec 4

10 – 11 am | Zoom

(send an email to ayabakan@temple.edu to get the Zoom link)

Abstact:

Social media has become a vital platform for voicing product-related experiences and concerns, which not only signal potential defects but also impose pressures on firms. This study scrutinizes the rarely-studied relationship between these voices and product recalls by focusing on the pharmaceutical industry since social media pharmacovigilance is becoming increasingly crucial for detecting drug safety signals. Using Federal Drug Administration (FDA) drug enforcement reports and social media data crawled from online forums and Twitter, we investigate whether social media can accelerate the product recall process in the context of drug recalls. The results, derived from the discrete-time survival analysis, suggest that more adverse drug reaction (ADR) discussions on social media would lead to a higher hazard rate of the drug being recalled, and, thus, a shorter time to recall. To better understand the underlying mechanism, we propose the information effect, which captures how extracting information from social media helps detect more signals and mine signals faster to accelerate product recalls, and the publicity effect, which captures how firms or government agencies are pressured by public concerns to initiate speedy recalls. This study offers new insights for firms and policymakers concerning the power of social media and its influence on product recalls.

October 12 – Alan Dennis to Present “Fake News on Social Media”

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Fake News on Social Media

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Alan R. Dennis

John T. Chambers Chair of Internet Systems

Kelley School of Business, Indiana University

Friday, October 12, 2018

10:30 AM – noon

Speakman Hall Suite 200

 

Abstract

Fake news on social media has received much media attention and many experts believe it influenced the 2016 US Presidential election and the 2016 Brexit vote. More than 60% of Americans consume news on social media, and 84% believe they can detect fake news. But can they? We studied the ability of experienced social media users to detect fake news, and how seeing news headlines – both real and fake – influenced their cognition. Only 18% of subjects could detect fake news better than chance; 82% of users could have made better judgments by flipping a coin. We found that confirmation bias dominates, with users essentially unable to distinguish real news from fake news, and that cognition is driven by how well a news headline aligns with the user’s prior political beliefs.

We conducted a series of studies examining different ways in which the social media user interface could be designed, including how news headlines are presented, and the effects of quality ratings. These different interface designs had different effects on the extent to which users believed social media stories, and how likely they were to read, like, comment on and share the stories.

Feb 8: Shawndra Hill to present on Talkographics: Using What Viewers Say Online to Calculate Audience Affinity Networks for Social TV-based Recommendations

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Shawndra Hill
Assistant Professor, OIM Dept
The Wharton School, University of Pennsylvania

February 8, 2013
Speakman Hall 200, 1000am – 1130am
Seminar Title : Talkographics: Using What Viewers Say Online to Calculate Audience Affinity Networks for Social TV-based Recommendations

Abstract
Viewers of TV shows are increasingly taking to online sites like Facebook and Twitter to comment about the shows they watch as well as to contribute content about their daily lives. We present a novel recommendation system (RS) based on the user-generated content (UGC) contributed by TV viewers via the social networking site Twitter. In our approach, a TV show is represented by all of the tweets of its viewers who follow the show on Twitter. These tweets, in aggregate, enable us to reliably calculate the affinity between TV shows and to describe how and why certain shows are similar in terms of their audiences in a privacy friendly way. This paper’s two main contributions are: 1) a new methodology for collecting data from social media — including information about product networks (or how shows are connected through users on a social network), geographic location, and user-contributed text comments — which can be used to generate affinity networks and test them; and 2) a new privacy friendly UGC-based RS that relies on all publicly-available text contributed by viewers, as opposed to only pre-selected keywords extracted from the UGC associated with the shows, a specific ontology or taxonomy, which makes our approach more flexible and generalizable than those used in any prior research. We show that our approach predicts remarkably well the TV shows that Twitter users follow. We also explain why the approach works so well: First, we show that the UGC reflects the demographics, geographic location, and psychographics of viewers, and coin the term talkographics to refer to descriptions of a TV show’s viewers — or in general any product’s audience — that are revealed by the words used in text messages sent by Twitter-using TV viewers; second, we show that Twitter text can represent many complex nuanced combinations of the demographic, geographic, and psychographic features of the audience; third, we show that we can use talkographic profiles to first calculate similarities between TV shows, then use these similarities reliably in RSs; we also show that our approach can be combined with a product association network approach to achieve even better recommendations; finally, we show that our text-based approach performs best for shows for which there is a demographic bias to the viewing audience compared to those that do not have a demographic bias. To demonstrate that our RS is generalizable, we apply the same approach to followers of clothing and automobile retailers.

 

Oct 19: Paul Leonardi to speak on Using Social Technologies to Learn “Who Knows What” and “Who Knows Whom” in the Organization

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Paul Leonardi
Pentair-Nugent Associate Professor
Kellogg School of Management, Northwestern University

October 19, 2012
Speakman Hall 200, 1000am – 1130am
Seminar Title :  Using Social Technologies to Learn “Who Knows What” and “Who Knows Whom” in the Organization

Abstract
In most discussions of intra-organizational knowledge sharing, the words “search” and “transfer” are never far apart. Organizational theorists normally presume that before knowledge can be transferred, someone has to find where that knowledge resides through an active search process. I propose an alternative antecedent to knowledge transfer than search by developing the concept of ambient awareness. Through routine exposure to ambient communication – communications happening around us that we don’t partake in, but that we can eavesdrop upon – we begin to learn who knows what and who knows whom. By developing ambient awareness, we are ready, when the time comes to request a knowledge transfer to simply ask the right person for it or for access to it – we don’t first have to engage in lengthy procedures to search for it, nor do we have to maintain dual networks that support search and transfer simultaneously. I propose that the use of social media tools within organizations can overcome problems associated with the development of ambient awareness because they make messages transparent and networks visible. Through our exposure to these transparent messages and visible networks we develop an awareness of who knows whom and who knows what.