[Air-L] Critical/opinion papers/articles on user engagement

[Thomas Ball]

Casting a wide net in the interpretation of 'user engagement' suggests
options related to engagement operationalized wrt keyword search activities
and wikipedia editing:

Sreenivasan, *Quantitative analysis of the evolution of novelty in cinema
through crowdsourced keywords*
https://www.nature.com/articles/srep02758.pdf?proof=true
*Abstract*
The generation of novelty is central to any creative endeavor. Novelty
generation and the relationship between novelty and individual hedonic
value have long been subjects of study in social psychology. However, few
studies have utilized large-scale datasets to quantitatively investigate
these issues. Here we consider the domain of American cinema and explore
these questions using a database of films spanning a 70 year period. We use
crowdsourced keywords from the Internet Movie Database as a window into the
contents of films, and prescribe novelty scores for each film based on
occurrence probabilities of individual keywords and keyword-pairs. These
scores provide revealing insights into the dynamics of novelty in cinema.
We investigate how novelty influences the revenue generated by a film, and
find a relationship that resembles the Wundt-Berlyne curve. We also study
the statistics of keyword occurrence and the aggregate distribution of
keywords over a 100 year period.


Metyan, et al., *Early Prediction of Movie Box Office Success Based on
Wikipedia Activity Big Data*
http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0071226&type=printable

*Abstract*
Use of socially generated ‘‘big data’’ to access information about
collective states of the minds in human societies has become a new paradigm
in the emerging field of computational social science. A natural
application of this would be the prediction of the society’s reaction to a
new product in the sense of popularity and adoption rate. However, bridging
the gap between ‘‘real time monitoring’’ and ‘‘early predicting’’ remains a
big challenge. Here we report on an endeavor to build
a minimalistic predictive model for the financial success of movies based
on collective activity data of online users. We show that the popularity of
a movie can be predicted much before its release by measuring and analyzing
the activity level of editors and viewers of the corresponding entry to the
movie in Wikipedia, the well-known online encyclopedia.


On Sun, Jul 1, 2018 at 11:36 AM, Lior Zalmanson <zalmanson at gmail.com> wrote:

> Hello,
>
> I'm teaching a seminar on "Understanding User Engagement" and while most
> studies will be more empirical work on the nature of online user behavior,
> I want to encourage discussions around critical notions of user engagement,
> social media, and online participation.
>
> I would love any recommendations you might have. Of course, I've added
> thinkers such as Lovink and Lanier, but I'm looking for as many points of
> view as possible, representing an array of cultures, genders, etc. They
> don't have to be academic journal papers. Articles in Wired/Atlantic and
> similar publications will be even better.
>
>
> Looking forward and thank you in advance,
>
> Dr. Lior Zalmanson, Assistant Professor
> Dept. of Information and Knowledge Management
> University of Haifa, Israel
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