\section{\datasetname Collection}\label{sup:data-collection}

\input{08-01-data-coll-details}


% We show our writing setups in Figure \ref{fig:all_interface} (in full) and \ref{fig:accordion_interface} (in chunks).


\section{Analyses}
We present further details of our demographic analyses, both between the author demographics and their language use (\S\ref{sup:liwc-author-res}) and between the author and reader demographics (\S\ref{sup:rater-author-traits}).

\subsection{Author demographics and topic choice}\label{sup:author-image-choice}
To ensure the validity of our other analyses, we examine whether an author's identity was associated with their choosing one of the five topics (Figure \ref{fig:all-prompts}).
We find that only an author's agreeableness affected their choice of image prompt, with highly agreeable authors preferring the dog story (Cohen's $d=0$.30, $p<0$.001; Figure \ref{fig:all-prompts}a) and low agreeableness authors preferring the jail story ($d=0$.41, $p<0$.001; Figure \ref{fig:all-prompts}b).
Other demographic variables were comparable for every image prompt (as measured by one-way ANOVAs.)



\subsection{Linguistic signal of author demographics}
\label{sup:liwc-author-res}
As described in \S\ref{ssec:author-analyses}, we first extract language categories from stories using the LIWC \cite{liwc2015} lexicon.
Then, we use a linear regression model to compute the association between the category and the author's demographics, using z-scored LIWC features for easier interpretation of the regression coefficients ($\beta$s).

\input{08-02-authorDemographics-LIWC-res}
Our findings, outlined in Table \ref{tab:liwc-author-res}, show that an author's identity and personality are somewhat associated with the types of stories they tell (controlling for the type of image prompt they used).
Men focused on describing characters (pronoun, social), specifically female characters, whereas women displayed more hierarchical logical storytelling \cite[Analytic;][]{pennebaker2014small}.
Controlling for gender, we find that older authors wrote more vivid stories with more emotional tone (Tone, Exclam), more friendship words, and more visual descriptions (percept). In contrast, younger authors wrote in a more past-focused way.

Controlling for age and gender, we find effects of the author's agreeableness and conscientiousness personality traits on the types of language used in stories. We don't see significant effects on the extraversion, openness, or neuroticism scales, likely due to our small sample size of 1.6k \cite[e.g., compared to the 75k users in][]{schwartz2013personality}.
Shown in Table \ref{tab:liwc-author-res}, less conscientious authors wrote more negative stories, whereas more conscientious authors were more positive and focused on character motivations (drives, reward).
Less agreeable authors used more swear words.

\subsection{Rater and author interaction}
\label{sup:rater-author-traits}
As explained in \S\ref{ssec:reader-analyses}, we analyze how rater and author traits relate to story ratings.
We run linear regression models using story ratings as dependent variables and rater demographics and personality traits as independent variables. We include author demographics and interaction features in these regression models to see if any shared traits across raters and authors were associated with rater preferences.
As in all previous analyses, we include story and image type in each model as controlling variables.
We report $p$-values and $\beta$ coefficients for each regression feature. 
Full details on the regression results are in Table~\ref{tab:dem-interaction}.

% We find that raters of age 45 and older rate stories as significantly less entertaining and like them less than those younger than 45. In additioan, we find that higher reader and author openness to experience scores are associated with higher creativity ratings, yet their interaction is negative.


\input{08-03-rater-author-trait-regression}

% \input{08-04-ratings-LIWC}


