February 2024 Meetup Blog

By Community Coordinators

Hacks/Hackers East Africa: Survey Programming using open-source tools (Pt 2)

Oluwafunmito Odefemi returned for the second session on the Kobo ToolBox with Hacks/Hackers East Africa

The Hacks/Hackers East Africa community, represented by 8 members, recently gathered in a virtual meetup for the 2nd in the series of the Kobo ToolBox training with Oluwafunmito Odefemi.

Hosted on 20 February 2024, Odefemi began the session with a recap of the practical session on survey programming using the Kobo ToolBox open-source platform conducted in January 2024. He walked the audience through the process he had mentioned for account creation on the platform, and the benefits of the toolbox to the audience.

Recap- The benefits include, but are not limited to:

1. Data visualisation in storytelling: The Kobo ToolBox assists in data collection, data management and visualising it in chart, maps and dashboards
2. Field reporting and surveys: The toolbox assists journalist in direct field data collection Conduct and Structure Interviews: It assists the journalist in conducting and structured interviews to collect structured data from respondents
3. Fact checking and verification: Assists in designing forms to collect and verify information
4. Election monitoring: Monitoring polling stations, tracking voter turn-out, and gathering election related data.

He commenced with the objective of the session by demonstrating methods of converting complex questions to forms, using an XLS form to add questions to the form, and export data via the Kobo ToolBox API.

1. Adding questions to the form.

In adding questions, the following steps should be used:

1. Select XLS sheet
2. Download the XLS form on your computer
3. Upload form containing survey questions onto the Kobo ToolBox (ensure form already contains question type, choice filters, templates etc). Uploading the form saves the user time as they do not have to create a survey from scratch, manually.
4. Once the file is uploaded you will have to provide a project name and description
5. The final step will be to ‘create a project’, after this the form will then load and display questions in sections format

He also shared ways to add the cascading feature to filter out options based on a user’s previous response. Citing his experience working on Agriculture projects, he created an option to calculate the revenue of sales made from certain agricultural products within the Kobo ToolBox form.

2. Accessing the form on a Mobile Device, the individual will have to open the KoboToolBox App and click the options on the right, settings > server. Then enter the following information.

1. URL:https://kc-eu.kobotoolbox.org/yourusername
2. Click on Get Blank Form. Kobo collect will connect to the server and show a list of all deployed forms
3. Select the form of interest and click on ‘Get selected’
4. Once the form is retrieved, click on Fill Blank Form to submit data

Following this demonstration the audience went through ‘some of the exciting features ’ of the Kobo ToolBox. These included the automating of responses. To activate this one needs to go to the ‘Data > downloads’ on their newly created form and activate the automatic settings then update the form.

In this session attendees learnt how to simplify their Kobo ToolBox experience in their quest to collect and analyse data, in various sectors.

Join Hacks/Hackers Africa to view this skills building session with Oluwafunmito Odefemi

Hacks/Hackers West Africa: Utilising data in combating gender misinformation

‘Gendered misinformation refers to false or misleading information that specifically targets or affects individuals based on their gender identity. It can be done unintentionally (misinformation) or intentionally (disinformation)’. This was the opening statement from Journalist and Fact-checker Chioma Iruke, during her virtual skills building session focusing on ‘Utilising data in combating gender misinformation’, on 28 February 2024.

Addressing an audience of 7, Iruke described some characteristic of gender misinformation as

1. Amplifying existing stereotypes, biases or discrimination e.g. women are weak, men are strong.
2. Targeting a particular gender
3. Limiting opportunities because of certain stereotypes or biases
4. Promoting harassment online and offline

Iruke shared an example citing the case of a newspaper article that circulated in the year 2020, during Covid19 in Nigeria. The article claimed that the Centre for Disease Control (CDC) had instructed all men to shave their beards, to protect themselves from being infected with Covid19.

However, upon fact-checking the article, it was discovered that this instruction was exclusively meant for CDC staff prior to covid, as an internal hygiene measure. This simply demonstrates how misinformation spreads like wildfire especially the unchecked ones.

Another example cited was that of a political female electoral figure in Rwanda who withdrew her place as a presidential running candidate at the elections due to the controversy of her exposed body being shared with the public.

This led to highlighting various ways to monitor mis/dis information which include:

1. Social media monitoring: Crowdtangle is a suggested tool for this activity.
2. Creating a bad actors list:This is described as watching certain accounts to monitor activity.
3. Monitoring the candidates:This involves focusing on social accounts with more than 500 followers to prevent uncontrollable spread of mis/dis information
4. Building a gendered lexicon
5. Key word searches: Using platforms such as Mentionayltics, comparing the context in which certain words were used vs the original meaning of the word

She then demonstrated how her team had built a gendered lexicon during the past elections, as captured in the image below.

Iruke explained how slangs were being manipulated and used in the wrong context to promote disinformation. Her team created the spreadsheet above to monitor which of these words were more or less prevalent during that election.

The role of Mentionalytics in assisting with periodic keyword tracking of mis/disinformation, and its ability to allow an individual download a detailed report for further analysis was shared by Iruke. She also commenced a demo showing the designs her team put together for the gendered lexicon to track keywords, shares and social media mentions for women in politics (as demonstrated in the screenshot below).

Backend of the mentionalytics, illustrating methods of setting up keyword tracking project, by focusing on certain keywords.

The information uploads and displays according to your preferred keyword tracking. In the above demo, there was no location restriction, and this enabled a wider data reach through the use of the keywords inputted.

The image above shows a demonstration of the use of Crowdtangle to track mis/disinformation

The Q&A session commenced with the audience asking Iruke steps a victim of mis/dis information can take to obtain justice? She responded stating that it might take a while for social media apps to take down the unpleasant comments, online bullying etc. But a viable measure is getting a ‘shared partner to advocate for the account to be taken down’ or installing a ‘Botometer’ on your X account to conduct findings to confirm if this is a human generated or a bot generated content person. If discovered to be human content, it is punishable by law and the individual can be sued.

Iruke’s session was informative and practical. It provided the audience with a hands-on experience of how to track mis/disinformation in this digital age. It further equipped the audience with resources to track malicious activity, and shared insight on next steps to obtain justice.

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