---
title: 'WeDo: Collective Action Platform'
url: https://www.emergentmind.com/topics/wedo
type: topic
---

# WeDo: Collective Action Platform

Searching arXiv for the cited WeDo paper to ground the article in the original source.
WeDo is a lightweight, domain-agnostic platform designed to support participatory, end-to-end collective action, defined as a process in which a crowd or community identifies opportunities, formulates goals, brainstorms ideas, develops plans, mobilizes, and takes action. Rather than addressing only a single stage such as issue reporting, crowdfunding, or scheduling, WeDo was developed to guide participants through the entire sequence from mission formation to coordinated action. Its central research contribution is to explore both the possibilities and the barriers of sociotechnical support for simple forms of collective action, especially through automated transitions across phases and through the reuse of existing social-media infrastructure [1406.7735].

## 1. Scope and objectives

WeDo was conceived to support a full collective-action workflow organized around a “mission.” In the system’s terminology, the mission is the focal opportunity or problem around which participation is organized. The intended process consists of identifying an opportunity or problem, setting a clear goal, brainstorming and surfacing ideas, planning by selecting one idea via community voting, mobilizing participants through notifications and reminders, and taking action together at a pre-specified time [1406.7735].

A defining characteristic of WeDo is its emphasis on participatory, end-to-end collective action. The platform does not merely collect proposals or tally preferences; it attempts to chain phases automatically so that a crowd can move from agenda formation to execution without requiring a separate tool at each step. The paper explicitly frames this as an attempt to reduce drop-off between stages, keep momentum high, and maximize the chance that community ideas become on-the-ground activities. This suggests a design orientation toward continuity of engagement rather than optimization of any single interaction primitive.

The system is also explicitly lightweight and domain-agnostic. No specialized application domain is assumed, and the same mechanism is applied to workshop activities, conference social events, book selection, and a student-led civic cleanup. A plausible implication is that WeDo is best understood less as a vertical application than as a reusable sociotechnical pattern for small-scale collective mobilization.

## 2. Architecture and technical substrate

WeDo consists of two core technical components: a Twitter bot, implemented as a standard Twitter app, and a complementary web interface [1406.7735]. The Twitter bot announces new missions via the mission creator’s account and the @WeDo account, listens for tweets with the mission’s hashtag during ideation and voting phases, counts retweets and favorites as proxy votes, and issues automated, time-triggered tweets to transition the group from ideation to voting, from voting to plan finalization, and from plan finalization to action reminders.

The web interface provides mission creation through a form that includes mission name, “this mission is important to me because…,” hashtag, idea-selection deadline, and action date. It visualizes ideas sorted by popularity as measured by retweets plus favorites, tracks the current phase and time remaining until the next phase, and lets users submit ideas or refine them in free text with the hashtag appended automatically. The interface is described as having a top panel with mission title, description, hashtag, countdown clock to voting close, announcement of selected plan, and action date/time; a middle panel with a text box for adding new ideas; and a bottom panel with a ranked list of submitted ideas showing retweet and favorite counts.

By building atop Twitter, WeDo leverages an existing social graph, simple in-line voting through retweet and favorite actions, ubiquitous mobile access, and an open API for bot-driven automation. That architectural choice is central to the system’s design logic: instead of constructing a standalone social environment, WeDo overlays collective-action orchestration on top of an existing communication platform. The paper’s discussion of trust and permissions later indicates that this choice also introduced constraints.

## 3. Interaction design and phase structure

WeDo organizes participation into distinct phases with corresponding affordances [1406.7735]. During mission creation, the web form prompts the creator for a mission name, personal motivation, unique hashtag, voting deadline, and action date. On submission, the system generates a 140-character proposed tweet linking to the mission page; the creator may edit and publish it.

During ideation, any Twitter user may tweet ideas using the mission hashtag or submit them through the web form. The web view lists all ideas, while mobile users can contribute directly through Twitter without visiting the site. During voting, after the ideation window closes, WeDo tweets a call to “retweet or favorite your top ideas by [time].” Participants then use Twitter’s built-in retweet and favorite actions as votes, and the web interface re-ranks ideas in real time by vote count.

Finalization and mobilization occur after voting closes. At that point, WeDo computes the winner and tweets a notification of the form “@WeDo participants, the top choice is X. Please suggest meeting details.” As the action date approaches, timed reminders are sent to the hashtag stream and follower lists. This sequence operationalizes a transition from open-ended proposal generation to convergence and then to logistical coordination.

The formal model given in the paper represents each mission as a tuple

$$
m = (h, t_0, t_v, t_a)
$$

where $h$ is the mission’s unique hashtag, $t_0$ is mission start time, $t_v$ is vote-closing time, and $t_a$ is action execution time. The idea set is defined as

$$
I(m) = \{\, i \mid i \text{ is a tweet or web submission with hashtag } h \text{ and timestamp } t_0 \le t < t_v \,\}
$$

and each idea $i \in I(m)$ accrues votes

$$
v(i) = RT(i) + Fav(i)
$$

where $RT(i)$ and $Fav(i)$ are retweet and favorite counts. The winner is

$$
i^* = \arg\max_{i \in I(m)} v(i)
$$

and the phase function is given as

$$
\phi(t) =
\begin{cases}
\text{Ideate}, & \text{if } t_0 \le t < t_v \\
\text{Vote}, & \text{if } t_v \le t < t_a - \Delta_{remind} \\
\text{Finalize}, & \text{if } t = t_v \\
\text{Action}, & \text{if } t \ge t_a - \Delta_{remind}
\end{cases}
$$

Transitions are triggered by simple clock events, and winner computation uses a max operator over vote counts. This formalization makes clear that the system’s orchestration logic is intentionally minimal: time-based state changes and social-media-native voting.

## 4. Pilot deployments

WeDo was deployed as a technology probe in three settings, each involving one mission and a complete traversal from proposal generation to a collective outcome [1406.7735].

| Setting | Metrics | Outcome |
|---|---|---|
| End-of-Workshop Celebration | 1 mission, 12 submitted ideas, ~50 voting actions, 15 participants engaged | Group voted to host an impromptu poster “lightning” session immediately |
| Conference Banquet Activity | 1 mission, 18 ideas, ~75 retweets/favorites, 40 unique voters | Voted for a “themed photo scavenger hunt,” which took place successfully |
| Twitter Book Club Selection | 1 mission, 25 book suggestions, ~120 votes, 60 people voting | Bestseller “The Circle” was selected; reading schedule set |

The End-of-Workshop Celebration involved 20+ attendees at a multi-day CS workshop and asked participants to decide how to wrap up the workshop. The Conference Banquet Activity involved 100 conference participants and was used to decide a fun side-event at the evening banquet. The Twitter Book Club Selection involved a public Twitter book club with approximately 200 followers and was used to choose the next book.

Across these pilots, roughly 20–60 participants per mission found submitting ideas and voting via Twitter intuitive. In each case, WeDo’s automated prompts kept the process moving, and all three missions reached a real-world or virtual collective action stage. The study therefore supports the narrower claim that simple automated orchestration can carry small groups through end-to-end action sequences, at least in bounded settings with relatively lightweight coordination requirements.

## 5. The #cleanerNYC case

A concrete case study in the paper is the student-led mission to “help make my city a cleaner place” using the hashtag #cleanerNYC [1406.7735]. In mission creation, the founder tweeted “Help make my city a cleaner place… #cleanerNYC” with a voting deadline 24 hours later and an action date. In ideation, within 2 hours, 30+ ideas appeared, including “Clean Battery Park,” “Adopt a block in Chinatown,” and “Park bench repaint.”

During voting, WeDo prompted “1 h left to RT or ♥ your favorite #cleanerNYC idea!” The idea “Clean Battery Park” received 17 votes. In finalization, WeDo announced the winner and asked for meeting-point details, after which volunteers specified “Meet by Korean War Memorial…” During action, reminders went out 1 hour before the event; 25 people showed up, cleaned the park, and shared photos back to the hashtag.

The case is important because it demonstrates the complete operational cycle in a public, place-based setting rather than in a workshop or conference environment. It illustrates how automated phase transitions, the lightweight user interface, and Twitter-native affordances can transform a rough idea into coordinated real-world action. At the same time, the need for volunteers to supply meeting-point details after winner selection indicates that even with automation, some planning work remains socially organized rather than systemically specified.

## 6. Challenges, limitations, and design implications

The deployments revealed several recurring challenges [1406.7735]. Participants were sometimes unsure whether a tweet was part of ideation or voting because both used the same hashtag, a problem described as phase fluidity and hashtag overload. Users also expected votes on near-duplicate ideas to merge, whereas WeDo treated each tweet as a separate ballot. Broad mission statements such as “make my city greener” left newcomers unsure how to contribute. Without explicit roles or tools for leaders to emerge, missions occasionally stalled in the Finalize stage. Requiring participants to remain involved across all four phases discouraged casual participants who wanted only to ideate or vote. Some users also hesitated to authorize WeDo’s Twitter app or share location data for offline meetups.

These observations led to several design implications. The paper argues that future systems should differentiate ideation, voting, and coordination streams more clearly, for example through separate hashtags or user-interface tabs. It also proposes automated clustering of semantically similar ideas and merging their vote tallies to reduce fragmentation. Additional implications include lightweight onboarding and “how to participate” guides, exemplar missions, features such as volunteer project leads or role assignments to support leadership, flexible participation paths that permit users to “just vote” or “just show up,” and privacy and trust controls such as read-only participation modes or clearer permission explanations.

Taken together, these findings position WeDo less as a finished solution than as a sociotechnical probe into end-to-end collective action. The system demonstrates that timed bots, hashtags, retweets, favorites, and a minimal web front end can scaffold the full cycle from problem identification through shared action. It also makes visible design trade-offs around phase separation, leadership, participation norms, and trust. A plausible implication is that the principal contribution of WeDo lies in exposing the coupling between algorithmic workflow management and the social contingencies of coordination: automation can sustain momentum, but it does not eliminate the need for role formation, norm negotiation, or selective participation.

Source: https://www.emergentmind.com/topics/wedo