What’s in an @reply? A case study of two-way communication in Target Canada’s Twitter @replies
Bibliographic record
Abstract
This paper analyzes the Twitter @replies (responses to a user’s initial tweet) of Target Canada as the organization entered the Canadian retail landscape in the Spring of 2013. The @replies posted by Target Canada are analyzed through two lenses: Grunig’s (1992) two-way symmetrical model of public relations and Kent & Taylor’s (2001) dialogic theory of public relations. Grunig’s model argues that the symmetrical model of communication serves the interests of both organizations and their publics by emphasizing dialogue and mutually beneficial relationships (Grunig & Jaatinen, 1999). Similarly, Kent & Taylor advocate for relational interaction and relationship building between organizations and their audience. This case study will contribute to the small body of literature that focuses on Twitter’s @reply function. As social media use is an increasingly important marketing and branding tool, it is important for organizations to realize the potential that each platform can offer. Through Twitter @replies, organizations can create a balanced dialogue (where both the organization and its public participate in a dialogic exchange) and build open, mutually beneficial relationships.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".