Data and code needed to reproduce the results of the paper "Effects of community management on user activity in online communities", available in draft here.

Instructions:

1. Unzip the files.
2. Start with JSON files obtained from calling platform APIs: each dataset consists of one file for posts, one for comments, one for users. In the paper we use two datasets, one referring Edgeryders, the other to Matera 2019.
3. Run them through edgesense (https://github.com/edgeryders/edgesense). Edgesense allows to set the length of the observation period. We set it to 1 week and 1 day for Edgeryders data, and to 1 day for Matera 2019 data. Edgesense stores its results in a file called JSON network.min.json, which we then rename to keep track of the data source and observation length.
4. Launch Jupyter Notebook and run the notebook provided to convert the network.min.json files into CSV flat files, one for each netwrk file
5. Launch Stata and open each flat csv files with it, then save it in Stata format.
6. Use the provided Stata .do scripts to replicate results.

Please note: I use both Stata and Jupyter Notebook interactively, running a block with a few lines of code at a time. Expect to have to change directories, file names etc.

This replication package contains the raw data and code to replicate the findings reported in the paper. The data are licensed under a Creative Commons Attribution 4.0 International Public License. The code is licensed under a Modified BSD License. See LICENSE.txt for details.

Software requirements

All analysis were done in Stata version 16:

Add-on packages are included in scripts/libraries/stata and do not need to be installed by user. The names, installation sources, and installation dates of these packages are available in scripts/libraries/stata/stata.trk.

Instructions

Save the folder ‘replication_PLOS’ to your local drive.

Open the master script ‘run.do’ and change the global pointing to the working direction (line 20) to the location where you save the folder on your local drive

Run the master script ‘run.do’ to replicate the analysis and generate all tables and figures reported in the paper and supplementary online materials

Datasets

Wave 1 – Survey experiment: ‘wave1_survey_experiment_raw.dta’

Wave 2 – Follow-up Survey: ‘wave2_follow_up_raw.dta'

Map: shape-files ‘plz2stellig.shp’ ‘OSM_PLZ.shp’, area codes ‘Postleitzahlengebiete-_OSM.csv’_, (all links to the sources can be found in the script ‘04_figure2_germany_map.do’)

Pretest: ‘pre-test_corona_raw.dta’

For Appendix S7: ‘alter_geschlecht_zensus_det.xlsx’, ‘vaccination_landkreis_raw.dta’, ‘census2020_age_gender.csv’ (all links to the sources can be found in the script ‘06_AppendixS7.do’)

For Appendix S10: ‘vaccination_landkreis_raw.dta’ (all links to the sources can be found in the script ‘07_AppendixS10.do’)

Descriptions of scripts

1_1_clean_wave1.do This script processes the raw data from wave 1, the survey experiment 1_2_clean_wave2.do This script processes the raw data from wave 2, the follow-up survey 1_3_merge_generate.do This script creates the datasets used in the main analysis and for robustness checks by merging the cleaned data from wave 1 and 2, tests the exclusion criteria and creates additional variables 02_analysis.do This script estimates regression models in Stata, creates figures and tables, saving them to results/figures and results/tables 03_robustness_checks_no_exclusion.do This script runs the main analysis using the dataset without applying the exclusion criteria. Results are saved in results/tables 04_figure2_germany_map.do This script creates Figure 2 in the main manuscript using publicly available data on vaccination numbers in Germany. 05_figureS1_dogmatism_scale.do This script creates Figure S1 using data from a pretest to adjust the dogmatism scale. 06_AppendixS7.do This script creates the figures and tables provided in Appendix S7 on the representativity of our sample compared to the German average using publicly available data about the age distribution in Germany. 07_AppendixS10.do This script creates the figures and tables provided in Appendix S10 on the external validity of vaccination rates in our sample using publicly available data on vaccination numbers in Germany.

Open data, commonly referred to by the English term "Open Data" even in the Italian context, are certain types of data that are freely accessible to everyone, without copyright restrictions, patents, or other forms of control that limit their reproduction. The opening of public databases promotes transparency, innovation, and efficiency in public administration and is an opportunity to create value-added services for high-performing and differentiated services and to help generate economic and business growth. With the "Open Data Project, the Useful Ones," the Municipality of Rimini aims to publish and share the Open Data held by the municipal administration to promote its dissemination, fostering policies of transparency, access, and participation. The project is part of the participatory path of the Digital Agenda of the Municipality of Rimini, the plan of which was approved with resolution G.C. n. 342 of 02/12/2014. https://sites.google.com/site/agendadigitalelocalerimini/piano The data opening process of the Municipality of Rimini, already started experimentally in previous years, has been defined with the approval of the opening strategy outlined in the "Guidelines for the reuse and dissemination of public data of the Municipality of Rimini" approved by the City Council with Resolution n. 270 of 11/08/2015, and with the establishment of the open data team through the formalization of a working group composed of contact persons identified within each Directorate, from which a path of involvement of the entire municipal administration was initiated, structured in the phases of awareness and reconnaissance of the entity's information assets to identify databases useful for publication. To this end, this online section "OPEN DATA Municipality of Rimini" has been implemented, created according to the standards set by the national Guidelines for the enhancement of public information assets, into which the datasets already published previously have been merged and where those of new identification or request will be published as they become available. The site is based on an open-source data cataloging software called CKAN, developed by the Open Knowledge Foundation: a non-profit organization that promotes free knowledge. Each entry contains a description of the data (metadata) and other useful information, such as available formats, the data holder, the license, and the topics that the data address. For geographic open data, the Geo open data web site http://data.sit-rimini.opendata.arcgis.com/, a section developed ad hoc by the Municipality of Rimini on the Esri's ArcGIS Online platform, which has made geographic open data more complete and usable, viewable in preview in graphic and tabular format, together with the metadata, can also be accessed from these pages. Send us suggestions, proposals and requests through the twitter, facebook, email channels. Translated from Italian Original Text: I dati aperti, comunemente chiamati con il termine inglese Open Data anche nel contesto italiano, sono alcune tipologie di dati liberamente accessibili a tutti, senza restrizioni di copyright, brevetti o altre forme di controllo che ne limitino la riproduzione. L'apertura delle banche dati pubbliche favorisce la trasparenza, l'innovazione e l'efficienza della PA ed è un'opportunità per creare servizi a valore aggiunto per prestazioni performanti e differenziate e per contribuire a generare crescita economica e d'impresa. Con il "Progetto Open Data, quelli utili" il Comune di Rimini si pone come obiettivo la pubblicazione e condivisione degli Open Data in possesso dell'Amministrazione comunale per promuoverne la diffusione favorendo politiche di trasparenza, accesso e partecipazione. Il progetto fa parte del percorso partecipativo dell' Agenda Digitale del Comune di Rimini il cui piano è stato approvato con deliberazione G.C. n. 342 del 02/12/2014. https://sites.google.com/site/agendadigitalelocalerimini/piano Il processo di apertura dei dati del Comune di Rimini, già avviato in fase sperimentale negli scorsi anni, ha avuto una sua definizione con l'approvazione della strategia di apertura delineata nelle "Linee guida per il riutilizzo e la diffusione dei dati pubblici del Comune di Rimini" approvate dalla Giunta Comunale con Deliberazione n.270 del 11/08/2015, e con l'istituzione del team open data avvenuta con la formalizzazione di un gruppo di lavoro composto da referenti individuati nell'ambito di ogni Direzione, a partire dalle quali è stato avviato un percorso di coinvolgimento dell'intera amministrazione comunale articolato nelle fasi di sensibilizzazione e ricognizione del patrimonio informativo dell'ente per poter individuare le banche dati utili alla pubblicazione. A tal fine è stata implementata questa sezione online "OPEN DATA Comune di Rimini", realizzata secondo gli standard fissati dalle Linee guida nazionali per la valorizzazione del patrimonio informativo pubblico, in cui sono confluiti i dataset già pubblicati in precedenza e dove verranno pubblicati man mano quelli di nuova individuazione o richiesta. Il sito è basato su un software opensource di catalogazione dei dati, chiamato CKAN, sviluppato dalla Open Knowledge Foundation: un'organizzazione noprofit che promuove il sapere libero. Ogni voce contiene una descrizione dei dati (metadati) e altre informazioni utili, come i formati disponibili, il detentore, la licenza e gli argomenti che i dati affrontano. Per gli open data geografici viene raggiunta da queste pagine anche la Geo open data web site http://data.sit-rimini.opendata.arcgis.com/ sezione sviluppata ad hoc dal Comune di Rimini sulla piattaforma Arcgis on line della Esri che ha reso gli open data geografici più completi e fruibili, visualizzabili in anteprima in formato grafico e tabellare, unitamente ai metadati. Inviateci suggerimenti, proposte e richieste attraverso i canali twitter, facebook,email.

Stata replication files for the online appendix. Twins data & codebook downloaded years ago from the University of Nebraska & converted to Stata. https://www.unl.edu/polphyslab/data Open MX replication files for the main text analysis. (Incomplete for now)

Replication package and online appendix for the paper “Output Divergence in Fixed Exchange Rate Regimes” by Yao Chen and Felix Ward. The replication package includes a readme-file, Stata codes, data, and output files required to reproduce all figures presented in the main text and Online Appendix.

The paper presents empirical evidence for the violation of nominal exchange regime neutrality. We find that fixing the exchange rate is associated with real output losses among countries with a high pre-peg inflation rate. In particular, ten years after fixing the exchange rate a country with a +1 percentage point (ppt) pre-peg wage inflation differential has a 2% lower real GDP per capita level and a 1% lower TFP level. The tradable sector is more affected than the non-tradable sector, which accords with the former’s greater exposure to international arbitrage.

The Oxford Internet Survey, 2009 is a representative survey of British internet use in 2009. Data were collected via in-home interviews with respondents and includes internet users, ex-users and non-users. It contains nearly 700 variables measuring internet activities, attitudes and effects.

Further information about the OxIS, including publications, is available from the Oxford Internet Surveys webpages.

Users should note the data are only available in Stata format.

This study is Open Access. It is freely available to download and does not require UK Data Service registration.

The COVID-19 Coping Study is a national, longitudinal cohort study of 6,938 US adults aged ≥55 enrolled from April 2nd through May 31st, 2020 in all 50 US states, the District of Columbia, and Puerto Rico. Participants were recruited through a non-probability multi-frame sampling strategy, and completed data collection through online questionnaires administered via the University of Michigan Qualtrics in English (N=6,886) and Spanish (N=52). Data were collected on a variety of demographic, social, and health-related topics including COVID-19 symptom and testing history, COVID-19-related stressors and worries, self-isolation and social distancing practices, behavior changes and coping mechanisms, mental health symptom scales, and living arrangements. A sub-set of the baseline sample (N=4,401) were sent monthly follow-up questionnaires over the following 12 months. The included files contain baseline through 6-month of follow-up data from the COVID-19 Coping Study. Data are available in Stata (C19CS.dta), a CSV file with value labels (C19CS Labelled.csv), and a CSV file with numeric values (C19CS Numeric.csv).

Abstract copyright UK Data Service and data collection copyright owner.The Oxford Internet Surveys (OxIS) is the longest-running academic survey of internet use in Britain, describing how internet use has evolved from 2003 to the present day. Run by the Oxford Internet Institute, a Social Sciences department at the University of Oxford, this survey provides unrivalled data, rigorous analysis and policy-relevant insights into key aspects of life online.OxIS is a multi-stage national probability sample of 2,000 people in Britain, enabling researchers to project estimates to the nation as a whole. Undertaken every two years since 2003, it surveys users, non-users, and ex-users, covering internet and ICT access and use, attitudes to technology, and supporting demographic and geographic information. The Oxford Internet Survey, 2003 (OxIS 2003) is a representative survey of British internet use in 2003. Data were collected via in-home interviews with respondents and includes both internet users and nonusers. The dataset contains 496 variables measuring internet activities, attitudes and effects.Further information about the OxIS, including publications, is available from the Oxford Internet Surveys webpages.Users should note the data are only available in Stata format.This study is Open Access. It is freely available to download and does not require UK Data Service registration. Main Topics: The data include a wide variety of items measuring issues related to internet use, including:social and political outlookinternet use and access internet use at work shopping on the internet attitudes of past users of the internet attitudes of those who have never used the internet demographic measures One-stage cluster sample Face-to-face interview: Paper-and-pencil (PAPI)

Abstract

The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 3-5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop
• Market

Universe

Members of the following households are not eligible for inclusion in the survey: • All people who live outside the selected EAs, whether in urban or rural areas. • All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks. • Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.) • Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.) • Non-Malawian tourists and others on vacation in Malawi.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS5 sampling frame is based on the listing information and cartography from the 2018 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS5 strata are composed of 32 districts in Malawi.

A stratified two-stage sample design was used for the IHS5.

Note: Detailed sample design information is presented in the "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

HOUSEHOLD QUESTIONNAIRE The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3 and IHS4 questionnaires. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS5 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).

AGRICULTURE QUESTIONNAIRE All IHS5 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS4, IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS5 cross-sectional households supply information on the last completed rainy season (2017/2018 or 2018/2019) and the last completed dry season (2018 or 2019) depending on the timing of their interview.

FISHERIES QUESTIONNAIRE The design of the IHS5 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS5 fishery questionnaire.

COMMUNITY QUESTIONNAIRE The content of the IHS5 Community Questionnaire follows the content of the IHS3 & IHS4 Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS5 community questionnaire was administered to each community associated with the cross-sectional EAs interviewed. Identical to the IHS3 and IHS4 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.

MARKET QUESTIONNAIRE The Market Survey consisted of one questionnaire which is composed of four modules. Module A: Market Identification, Module B: Seasonal Main Crops, Module C: Permanents Crops, and Module D: Food Consumption.

Cleaning operations

DATA ENTRY PLATFORM To ensure data quality and timely availability of data, the IHS5 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS5, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar – checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS5 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.

DATA MANAGEMENT The IHS5 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS5 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data