Sms 2017-momentary-talk-for-slideshare

@dan_suthers #SMSociety - 1

Twitter Issue Response Hashtags as Affordances for Momentary Connectedness

Chamil Rathnayake Department of Media, Middlesex University, London

Dan Suthers Department of Information and Computer Sciences

University of Hawai‘i, Honolulu

@dan_suthers #SMSociety

… a step beyond the paper …


Motivations & Preview Reliance on models of offline phenomena to study collective online behavior !  + Bootstrapping; Relating to prior literature !  - Mismatch to uniquely online interactional affordances and phenomena !  grounding constraint” (Clark & Brennan); sociotechnical

affordances; (boyd; Resnick) !  Need “digitally native” conceptions Issue-response networks as Momentary Connectedness

Uptake as concept for analyzing how tweets construct such networks


An Issue Response Network !  IRN: Networks defined by hashtags created in response to issue or event

!  #NepalEarthquake Data !  One week after April 25 2015 event

!  NodeXL Twitter API plugin !  Nodes: 15,118 tweets with #NepalEarthquake

!  Edges: 16,107 edges for RT and @reply

!  1898 original tweets


Models from Offline Settings !  Public Sphere

!  Interaction, formation of public opinion, rational-critical discussion, monitoring of authority

!  Applications to online settings are polymorphic, ranging in size and how closely bound vs. imagined

!  Publics !  Well defined boundaries; shared special interest and develop

expertise !  Fluid online communication blurs private and public and

offers range of interactivity !  Communities

!  Cohesion, collective identity, development of norms !  Generally smaller groups of social media users !  Some features not seen in larger issue-response networks


Digitally Native Models !  Connected Presence (Licoppe & Smoreda 2005)

!  maintaining close relationships when physically apart !  Public Sphericules (Gitlin, 1998; Holmes 2002)

!  constructing publicness in segmented ‘multicultural’ spheres with unique dynamics

!  Digital Togetherness (Marino 2015) !  sense of belonging and identity based on sharing experiences

!  Ad-hoc Publics (Bruns & Burgess; Bruns & Moe) !  discursive communities around a central shared interest

!  Personal Publics (Schmidt 2014) !  personal relevance, explicit ties, conversational

!  Imagined Audiences & Communities (Litt 2012, Marwick & boyd, 2011; Gruzd et al., 2011) !  fills in for missing cues about actual audience !  varies from specific persons to abstract audiences


Layers of Communication (Bruns & Moe) A tweet can be polymorphic across layers: !  macro: #hashtags " ad-hoc publics

!  rapidly formed and dissolved !  imagined audience

!  meso: follower networks " personal publics !  gradually formed, stable

!  micro: @mention & @reply " interpersonal communication !  ephemeral !  more transactive: actual audience

!  Suggests simultaneous forms of publicness based on Twitter affordances


Fit to #NepalEarthquake Questionable fit of above models to network as a whole, except polymorphic audiences (real and imagined) over layers of communication

!  Public sphere: rational discussion over time? !  Publics: well defined boundaries, domain specific

expertise? !  Community: cohesion, collective identity, sustained

practices? !  Connected presence: continuous close relationship? !  Digital togetherness: sharing experiences? !  Personal publics: follower-level, conversational? We do find a variety of sub-networks …


(Methodological aside) !  The Louvain community detection algorithm was used to find the following clusters !  Louvain performs well on benchmarks and in our prior work has yielded interpretable partitions (Suthers et al., HICSS 2013)

!  Another strong contender, InfoMap, produces similar but finer partitions due to Louvain’s resolution limit and InfoMap’s horizon limit (Barabasi, 2016; Suthers HICSS 2017)

!  Point is that clusters like the following can be found in the network, not to claim it is the only or best partitioning


Polymorphism: Fan Cluster !  947 nodes, 949 edges !  Transitivity & CC ~ 0 (no “conversation”)

!  Tweet by One Direction retweeted by fans

!  Digital activism through information sharing RT @onedirection: To

help those affected by the devastating earthquake in Nepal text: DONATE5 to 70008 and give £5. Thank you #NepalEarthquake


Polymorphism: Non-profit Cluster !  619 nodes, 873 edges !  Average degree 1.41 !  Average local CC 0.366 !  9/15 top nodes by degree are NGOs (World Vision Australia, Australian Red Cross, UNICEF, Nepal Red Cross …)

!  Minimally discursive ad-hoc public, similar to offline issue public, but on accelerated time frame and expanded geography

RT @UNrefugees: Please donate to provide urgent relief to victims of the #nepalquake #NepalEarthquake http://t.co/CNc4KOm2p8 http://t.co/Fs…


Polymorphism: News Cluster !  505 nodes, 690 edges !  Average degree 1.366 !  Average local CC 0.1 !  Most central nodes are news organizations: The Hindu, Indian Express, Times Now, Ani_news

!  Primary function: RT to share information, serving as community filter (Kwak et al. 2010)

RT @TimesNow: UN Secretary General Ban Ki-moon thanks first responders of the #NepalEarthquake


What defines #NepalEarthquake space? !  A collection of disjoint spaces?

!  78.6% of the 15118 nodes are in the largest WCC (shown): the prior examples are connected

!  We can find some existing models in the network, but what is the network?


Momentary Connectedness Polymorphic computer mediated publicness Structural !  # mobilizes and focuses collective activity

!  Prompt: Invites further comment on topic !  Space: Makes contributions mutually visible !  “Immutable mobile" (Latour, 1986)

!  Further structured via other Twitter affordances (boyd; Bruns & Moe)

Phenomenological !  Seeking to feel connected to others !  Imagined as well as actual audiences


Enacting Momentary Connectedness Clusters in networks of MC !  Polymorphic in size, duration, public and private visibility, interactivity

!  Bound together via use of hashtag A process (rather than categorical) perspective: !  What kinds of collective phenomena are actors constructing within this network? !  ANT (Latour, 2005) & SI (Fernback, 2007)

!  How do they use the affordances of the medium to do so?

Individual tweets provide evidence


Need for generalized unit of (inter)action To construct an account of how individual acts construct momentary connectedness !  Need analytic concept to understand internal structure of acts

!  and how they aggregate in networks !  Work with various media and media affordances

!  Work with full range of communicative intents (interactivity, transactivity, etc.)


Uptake Similar need in CSCL !  Unit capturing how dialogue

is distributed across media (e.g., chat, whiteboard)

!  Not assuming media properties ("adjacency pairs") or intent ("reply”)

Relationship present when an actor’s media coordination takes traces of prior or ongoing events as having relevance for present activity (Suthers, 2006; Suthers et al., 2010)

•  Examples: using #hashtag, RT, using @handle


Uptake needs a Twin: Projected Uptake Analytically, uptake looks backwards !  SMS literature on audiences looks forward, projecting to future acts

Networks are phenomenological !  Includes expected future extensions of the structure

!  In choice of content, #, @ a tweet offers affordances for future uptake (cf. Bruns’ levels)

Let's call this Projected Uptake !  (Aside: inspired by but ≠ CA projectability)


Tweets Contextualized with Uptake Consider the layers (Bruns & Moe): !  macro: #hashtags " ad-hoc publics !  meso: follower networks " personal publics !  micro: @handle " interpersonal communication Generalizing:

Uptake " Projected Uptake Unpacking: Prior Affordances " Uptake in Tweet " Constructed Affordances " Audience implied

Consider tweets in terms of this model


Uptake analysis of Tweets: New Tweet Uptake of hashtag (and external issue/event) Really difficult day yesterday. ..in addition to aftershocks. ..rainfall. ...too much hardship #NepalEarthquake !  No explicit evidence of interactional intent: not public sphericule or personal public

!  May or may not intend future uptake: imagined audience, personal public

Let's pray for the victims and their families in Nepal... #NepalEarthquake #PrayforNepal http://t.co/QKeGyY5Mc3“ !  "Let's pray": abstract audience

Projected uptake: tweet and hashtag(s)


Uptake analysis of Tweets: RT Uptake of prior tweet (and its author) RT @eoiktmnp: 14 civilian flights-7 schleduled, 7 special to operate today from Kathmandu to Delhi @MEAIndia #nepalearthquake

RT @eoiktmnp: Buses from Pokhra to Raxaul and Kathmandu to Gorakhpur will also evacuate Indian citizens @meaindia #nepalearthquakeIndicates relevance of taken-up tweet !  Begins to form collective activity, but only quasi-interactional

!  Projected uptake: tweet, hashtag, handle(s)


Uptake analysis of Tweets: @handle Uptake of (prior or external) actor using @ affordance (reply, mention) @LionelRichie will you come to simg at a #comcertforkatmandu? #nepalearthquake

@wailers, we're raising funds for #NepalEarthquake at http://t.co/vuFU2SD5CG& would love your support in spreading the word!

@derick4Him can you pray that he can be found please?? #NepalEarthquake https://t.co/1vvqdL9Q8U

!  Projected uptake: tweet, hashtag(s), handle !  More explicitly transactive to primary audience !  Others may also be imagined/intended


Schematic Summary Building larger structures out of tweets: !  Prior Affordances " Uptake in Ego Tweet " Constructed Affordances " Audiences implied


Summary Need for digitally native conceptions !  Uptake: a unit of analysis without assuming media or type of relation

!  User-constructed affordances for projected uptake evidence intended audience

Issue-response networks don't fit prior ideas of publicness

!  Momentary Connectedness a better fit !  Based on uptake of # and projected uptake of those tracking the hashtag

!  Both structural and phenomenological


Looking Forward Research potential: !  What kinds of sub-networks are found in momentary connectedness networks

!  How they interact and evolve over time !  How they emerge from voices of actors (polyphonic analysis, Trausan-Matu)

Uptake and projected uptake !  Generalized/neutral relations for analysis !  Apply to other kinds of networks, not just momentary connectedness in Twitter


Mahalo!

Dan Suthers [email protected]

@dan_suthers

Chamil Rathnayake [email protected]

Social Media

Sms 2017-momentary-talk-for-slideshare