3 Data
We created the shiny-app to pre-process the raw data (which is tabular but also contains columns with JSON formatted data to describe the participant\(\times\)post-level observations).
The shiny-app requires you to upload your raw DICE data and transforms its wide to a long format. It then provides a download-button. Below, we briefly describe the raw data before we turn our attention to the output of the shiny-app, that is, the processed data. In both sections, we use the data collected in Case Study 1 and anonymize the Prolific IDs (called participant labels).
3.1 Raw Data
While creating an experimental session, the DICE web app returns session code such as r5fbdbr1, for instance. It will also create a url containing that session code (e.g., https://ibt-hsg.herokuapp.com/SessionStartLinks/r5fbdbr1) directing you to you oTree interface, where you can monitor the session or download the data. After clicking on the Data tab, you can download the raw data by clicking on the Plain button in the bottom right of her screen. This will generate a csv file called all_apps_wide_YYYY-MM-DD.csv.
This data follows oTree’s conventions as displayed in Table 3.1.1
| participant.id_in_session | participant.code | participant.label | participant._is_bot | participant._index_in_pages | participant._max_page_index | participant._current_app_name | participant._current_page_name | participant.time_started_utc | participant.visited | participant.mturk_worker_id | participant.mturk_assignment_id | participant.payoff | participant.finished | session.code | session.label | session.mturk_HITId | session.mturk_HITGroupId | session.comment | session.is_demo | session.config.study_name | session.config.name | session.config.dwell_threshold | session.config.eMail | session.config.channel_type | session.config.data_path | session.config.show_cta | session.config.search_term | session.config.participation_fee | session.config.sort_by | session.config.copy_text | session.config.condition_col | session.config.delimiter | session.config.full_name | session.config.url_param | session.config.briefing | session.config.cta_text | session.config.real_world_currency_per_point | session.config.topics | session.config.title | session.config.survey_link | session.prolific_completion_url | session.completion_code | DICE.1.player.id_in_group | DICE.1.player.role | DICE.1.player.payoff | DICE.1.player.feed_condition | DICE.1.player.sequence | DICE.1.player.scroll_sequence | DICE.1.player.viewport_data | DICE.1.player.rowheight_data | DICE.1.player.likes_data | DICE.1.player.replies_data | DICE.1.player.promoted_post_clicks | DICE.1.player.touch_capability | DICE.1.player.device_type | DICE.1.player.screen_resolution | DICE.1.group.id_in_subsession | DICE.1.subsession.round_number | DICE.1.subsession.feed_conditions | DICE.1.subsession.FEED |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5 | jyri7zu8 | …37e56 | 0 | 4 | 5 | DICE | D_Redirect | 2024-10-15 14:44:20 | 1 | NA | NA | 0 | 1 | z2q0bsds | NA | NA | NA | NA | 0 | Social Media Study | 50 | hauke.roggenkamp@unisg.ch | https://raw.githubusercontent.com/Howquez/DICE/refs/heads/main/studies/meme_feed/stimuli/9gag.csv | 0 | (9GAG?) | 0 | sequence | NA | condition | ; | Hauke Roggenkamp | PROLIFIC_PID | NA | 1 | 1 | Mr. | https://unisg.qualtrics.com/jfe/form/SV_3OwkoxA4EbDFxxI | https://app.prolific.com/submissions/complete?cc=CJ2MHZVY | CJ2MHZVY | 5 | NA | 0 | A | 20, 36, 34, 26, 16, 13, 4, 3, 5, 15, 39, 2, 32, 1, 24, 6, 22, 11, 37, 29, 18, 35, 31, 9, 21, 14, 28, 19, 25, 27, 33, 30, 10, 23, 17, 8, 7, 12, 40, 38 | is-i36-i34-i34-i34-i3-i3-i2-i29-i37-i37-i18-i29-i29-i29-i29-i18-i35-i35-i18-i18-i18-i29-i37-i37-i11-i11-i22-i22-i22-i22-i22-i22-i22-i22-i22-i6-i1-i1-i15-i3-i3-i13-i31-i21-i21-i21-i14-i14-i28-i28-i19-i19-i25-i25-i25-i30-i23-i10-i10-i10-i10-i10-i10-i23-i17-i17-i17-i12-i12-i40-i40-i40-i38 | 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| 6 | 2oudny1t | …4d647 | 0 | 4 | 5 | DICE | D_Redirect | 2024-10-15 14:47:58 | 1 | NA | NA | 0 | 1 | z2q0bsds | NA | NA | NA | NA | 0 | Social Media Study | 50 | hauke.roggenkamp@unisg.ch | https://raw.githubusercontent.com/Howquez/DICE/refs/heads/main/studies/meme_feed/stimuli/9gag.csv | 0 | (9GAG?) | 0 | sequence | NA | condition | ; | Hauke Roggenkamp | PROLIFIC_PID | NA | 1 | 1 | Mr. | https://unisg.qualtrics.com/jfe/form/SV_3OwkoxA4EbDFxxI | https://app.prolific.com/submissions/complete?cc=CJ2MHZVY | CJ2MHZVY | 6 | NA | 0 | A | 10, 34, 24, 22, 39, 17, 15, 21, 9, 31, 14, 38, 12, 5, 35, 11, 40, 23, 28, 32, 36, 2, 8, 20, 33, 7, 27, 16, 1, 13, 30, 19, 25, 26, 18, 3, 4, 37, 29, 6 | is-i10-i10-i10-i10-i10-i10-i10-i34-i10-i34-i34-i34-i34-i24-i24-i22-i22-i39-i39-i17-i15-i21-i21-i9-i9-i31-i31-i31-i14-i14-i38-i12-i12-i5-i5-i35-i11-i40-i23-i28-i32-i36-i2-i2-i8-i20-i20-i33-i7-i27-i6 | 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| 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| 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| 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| [{““doc_id”“:39,”“clicked”“:false},{”“doc_id”“:38,”“clicked”“:false},{”“doc_id”“:40,”“clicked”“:false},{”“doc_id”“:36,”“clicked”“:false},{”“doc_id”“:37,”“clicked”“:false}] | 0 | Desktop | 1920x1080 | 1 | 1 | <itertools.cycle object at 0x7fb118acf880> | DICE/T_Feed_Twitter.html |
3.2 Processed Data
The data we show below has a nested structure as it shows observations on the participant\(\times\)post-level.
| session_code | participant_code | participant_label | participant_time_started_utc | touch_capability | device_type | condition | doc_id | displayed_sequence | seconds_in_viewport | scroll_sequence | liked | reply | hasReply | height |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 17 | 35 | 3.368 | 79 | FALSE | FALSE | 479 | |
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 8 | 36 | 2.417 | 80 | FALSE | FALSE | 456 | |
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 7 | 37 | 4.411 | 81 | FALSE | FALSE | 519 | |
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 12 | 38 | 5.179 | 82 | FALSE | FALSE | 454 | |
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 40 | 39 | 2.402 | 83 | FALSE | FALSE | 578 | |
| z2q0bsds | jyri7zu8 | …37e56 | 2024-10-15 14:44:20 | TRUE | Tablet | A | 38 | 40 | 1.968 | 84 | FALSE | FALSE | 578 | |
| z2q0bsds | 2oudny1t | …4d647 | 2024-10-15 14:47:58 | FALSE | Desktop | A | 10 | 1 | 3.746 | 1 | FALSE | FALSE | 530 | |
| z2q0bsds | 2oudny1t | …4d647 | 2024-10-15 14:47:58 | FALSE | Desktop | A | 34 | 2 | 13.087 | 3 | FALSE | FALSE | 169 | |
| z2q0bsds | 2oudny1t | …4d647 | 2024-10-15 14:47:58 | FALSE | Desktop | A | 24 | 3 | 5.362 | 2,4 | FALSE | FALSE | 520 | |
| z2q0bsds | 2oudny1t | …4d647 | 2024-10-15 14:47:58 | FALSE | Desktop | A | 22 | 4 | 6.845 | 5 | FALSE | FALSE | 553 | |
| z2q0bsds | 2oudny1t | …4d647 | 2024-10-15 14:47:58 | FALSE | Desktop | A | 39 | 5 | 3.642 | 6 | FALSE | FALSE | 440 |
Table 3.2 presents a code-book that describes the variables presented above.
| Scope | Variable | Type | Example | Description |
|---|---|---|---|---|
| Session | session_code | text | z2q0bsds | Unique session identifier. |
| Participant | participant_code | text | jyri7zu8 | Unique participant identifier generated by oTree. |
| Participant | participant_label | text | 4d647 | Unique participant identifier passed from Prolific (PID). |
| Participant | participant_time_started_utc | text | 2024-10-15 14:47:58 | Date and time the participant started the study. |
| Participant | touch_capability | boolean | FALSE | Describes whether the participant’s device was recognized as a touch device. |
| Participant | device_type | boolean | Desktop | Describes whether the participant’s device was recognized as a Desktop/Tablet/Mobile device. |
| Participant | condition | text | A | Condition name the researcher created in her stimuli csv file. |
| Post | doc_id | text | 34 | Unique social media post identifier the researcher specified in her stimuli file. |
| Participant x Post | displayed_sequence | numeric | 2 | The position in which a feed was displayed within the feed. |
| Participant x Post | seconds_in_viewport | numeric | 13.087 | |
| Participant x Post | scroll_sequence | text | 2, 4 | Describes the sequence in which a participant browsed through the social media post. May contain multiple integers if a participant browsed back and forth. |
| Participant x Post | liked | boolean | TRUE | Describes wheter a participant liked a social media post. |
| Participant x Post | reply | text | This is a comment. | Describes what a participant commented on a social media post. NA if nothing. |
| Participant x Post | hasReply | boolean | TRUE | Describes wheter a participant commented on a social media post. |
| Participant x Post | height | numeric | 520 | Describes the vertical resolution (height measured in pixel) in which a post was rendered on the participant’s screen. |
3.3 Additional Processing
Importantly, none of the two datasets presented here contains any self-reports. To generate you final dataset which includes behavioral measures, the stimuli, as well as self-reports, we advise you to merge the processed data with two other data sources. First, merge the shiny app’s output with your survey data using the participant_label as a key. Because the DICE app passes that ID to your survey tool, both datasets have these information. Second, merge that data with you stimuli csv (see Chapter 1) based on the doc_id and condition, if applicable.
Using R and the {data.table} package, this process looks as follows:
output <- data.table::merge.data.table(x = dice,
y = qualtrics,
by = "participant_label")
final <- data.table::merge.data.table(x = output,
y = stimuli,
by = c("doc_id", "condition"))
setorder(final, participant_code, displayed_sequence)