In T328597#8704350, @Anju_Maurya wrote:

Hello Everyone!
I am Anju Maurya, an Outreachy applicant from India. I am glad to be a part of this awesome community. I would like to contribute to "Research imbalances in translation between languages on Wikipedia" project. Can I start here by attempting the microtasks mentioned above?

Welcome @Anju_Maurya Yes you can start working on the microtasks that are mentioned above.

Hello. My name is Muhammad Romy Ardianto. I'd like to ask recomendation project because I am interest for being Wikimedia contributor. I am also interest to do like PHP, HTML, CSS, JS which are probably available on this Wikimedia project even though I have small knowledge about them. Then, what should I do for Wikimedia project then ?

Really thank you for your advice.

@Ardiy1: Hi, please see the red box at the top of this task where to bring up such questions. Thanks a lot!

@jan Hi Thank you for you feedback on my work. I will like to know the next step. Thank you

Hi everyone. I am Zepha, an Outreachy intern from Uganda and I'm excited to be a part of this community. I look forward to working with all of you and making meaningful contributions to Wikimedia.

In T328597#8711385, @Zepha_W wrote:

Hi everyone. I am Zepha, an Outreachy intern from Uganda and I'm excited to be a part of this community. I look forward to working with all of you and making meaningful contributions to Wikimedia.

Welcome Zepha. Good to have you here. To start contributing to this project, you can scroll up, view more about this project and see several mini-tasks you can contribute to.

Hello everyone. Happy new week. I hope you all are doing great.

@awight @Simulo , Please I have a few concerns

After contributing to any of the microtasks above, how do I know if it was accepted?

Is there any other thing I am to do after contributing?

@986_875_764: Hi, best to ask general process questions in Zulip, as they are not about Research into translation imbalances. See the box at the top of this page. Thanks! :)

In T328597#8714075, @986_875_764 wrote:

Hello everyone. Happy new week. I hope you all are doing great.

@awight @Simulo , Please I have a few concerns

After contributing to any of the microtasks above, how do I know if it was accepted?

Is there any other thing I am to do after contributing?

Hello, @986_875_764

I know it may be frustrating to get started and the Zulip chat does not offer immediate information about these basic details, or about the final contribution, so I will help. Please make sure to post your question there and wait until there is a response to follow the general rules. It may take some time. Just to help you get started, you are not accepted after making a contribution to a specific task because everyone can make a contribution and mentors can (sometimes) provide feedback on how you are doing when you specifically ask them to do so in the subtasks channels/forums.

So, make one or many contributions, as you see fit, post your contributions to the respective subtasks pages to ask for feedback (if you want to), and add your contribution via the Outreachy portal https://www.outreachy.org/dashboard/, there you will also see several options to submit a final application and answer some questions. You will only know if you are accepted as an intern by the end of the review period, by May 4, when all interns will be announced. Do check the timeline: https://www.outreachy.org/apply/project-selection/.

In T328597#8714075, @986_875_764 wrote:

Hello everyone. Happy new week. I hope you all are doing great.

@awight @Simulo , Please I have a few concerns

After contributing to any of the microtasks above, how do I know if it was accepted?

Is there any other thing I am to do after contributing?

@986_875_764 Just adding one more point to what @Ahn-nath just informed you about. If you meant to ask whether or not your task specific contribution was accepted, I think we'll have to wait for the mentors to decide the criteria for that. As in a similar query that I raised a few days ago our mentor informed that they are yet to decide a uniform criteria to count a task completion as accepted. For reference you may refer to the conversations Here. Hope it helps.

Thank you @Ahn-nath , @Abhishek02bhardwaj . I appreciate

i wanted to take on a task ho do i do that

i would like to tackle task T328597how do i do that

In T328597#8726402, @Theodorahmbedzi8 wrote:

i wanted to take on a task ho do i do that

@Theodorahmbedzi8 hi! In the description of this task you can see several microtasks, You can go to any of them and contribute. For how to contribute refer to the respective task descriptions.

@Theodorahmbedzi8: Please thoroughly read the red box and its links, and please ask general questions in Zulip instead. Thanks!

Sorry still struggling when it comes to contributions

Areas where translation imbalances are most likely to happen should be highlighted: The objective of this study is to pinpoint the precise categories of content or features in a good or service that are most likely to be impacted by imbalances in translation, such as user interface components, error messages, or written instructions. This is an important task because it will help to focus efforts on improving the translation quality in those areas and ultimately reduce language imbalances.
To accomplish this objective, the study may involve a number of different research methods, such as analyzing data on user behavior and preferences, conducting surveys or interviews with users, or using machine learning or natural language processing techniques to identify patterns and trends in translation quality.
By pinpointing the precise categories of content or features in a good or service that are most likely to be impacted by imbalances in translation, the study can provide valuable insights into the factors that contribute to language imbalances and help to inform targeted interventions to address these imbalances. For example, the study may reveal that certain user interface components or error messages are consistently poorly translated across different languages, suggesting a need for more robust translation tools or increased attention to these areas by translators and editors.
Overall, the objective of the study is to identify specific areas where translation imbalances are most likely to occur and provide actionable insights for addressing these imbalances and promoting more equitable access to information across languages.

Understanding how translation imbalances affect user experience, for as by leading to confusion or annoyance, and quantifying the impact on user satisfaction and engagement are the two main objectives of this research.
Develop tactics to address imbalances in translation: The objective of this study is to create strategies that are efficient in resolving imbalances in translation, such as enhancing the translation procedure, offering better training for translators, or putting in place automated quality control procedures.
Test the efficacy of various strategies for resolving translation imbalances: The objective of this study is to evaluate the efficacy of various strategies for resolving translation imbalances in terms of enhancing user experience, such as through A/B testing or usability testing.
Improving the quality of translated information requires first identifying the areas where translation imbalances are most likely to occur. Here are some instances of translation imbalances that could happen:
User interface Elements: A product or service's user interface includes elements like buttons, labels, and menus. Although these components are frequently brief and straightforward, even minor translation mistakes or inconsistencies can cause consumers to become confused or misunderstand the message.
Error messages: Error messages are a crucial component of the user experience since they let users know when something is wrong and offer feedback. However, improperly translated error messages may be challenging to comprehend and may not contain all the required details to guide users in fixing the problem.
Terms and jargon used in the technical field: It might be challenging to translate jargon and technical terminology when the target language lacks an equivalent. Users may find it challenging to grasp the product or service as a result of inconsistencies or errors in the translated information.
Cultural allusions: It might be challenging to interpret precisely cultural references like idioms, comedy, or historical events. Sometimes a cultural allusion is missing or has a different meaning or connotation in the target language. Users may become perplexed or misunderstand the situation as a result.
Materials for marketing and branding: Slogans, taglines, and advertising copy are just a few examples of marketing and branding materials that are intended to convey a certain message or tone. However, when translating these resources, cultural differences must be carefully taken into account guarantee that the intended message is successfully communicated, language nuances should be used.

 
Research Objectives:
• To identify the languages with the most and least number of articles on Wikipedia.
• To assess the quality of translation across different language versions of Wikipedia.
• To explore the factors that may be contributing to the imbalance in the number and quality of articles available across different languages.
• To identify potential solutions for addressing language imbalance on Wikipedia.
Obtain an API key: You will need an API key to use the Wikimedia API. You can obtain a key by creating an account on Wikimedia's developer portal.
Define the parameters: You will need to define the parameters for the API query to specify which data you want to retrieve. In this case, you will want to retrieve the number of articles available for each language version of Wikipedia. The API query should look something like this:
DATA COLLEFTION ADDING IN LANGUAGE IMBALANCE

1. Collect data on the number of articles available on Wikipedia for different languages. This can be done using the Wikimedia API or other data sources

CODE
https://[language_code].wikipedia.org/w/api.php?action=query&meta=siteinfo&siprop=statistics&format=json
Replace [language_code] with the language code of the Wikipedia version you want to retrieve data for (e.g. "en" for English, "es" for Spanish, etc.).
Send the API request: Send the API request using your API key and the API query parameters you defined. You can use a programming language like Python to automate this process.
Parse the data: The API will return a JSON file with the statistics for the requested Wikipedia version. You can parse this data to extract the number of articles available for that language version.
Repeat for other languages: Repeat the process for other language versions of Wikipedia to collect data on the number of articles available for each language.
Alternatively, you can also use other data sources such as the Wikipedia Statistics page (https://stats.wikimedia.org/#/all-projects) which provides data on the number of articles available for each language version of Wikipedia. You can extract this data manually or using web scraping tools.

2. Evaluate the quality of translation for a sample of articles across different language versions of Wikipedia. This can be done by recruiting bilingual volunteers to review and evaluate the translation quality of articles in different languages

a) Select the articles: First, select a sample of articles that are available in multiple language versions of Wikipedia. You can use the Wikimedia API or other data sources to identify such articles.

b) Recruit volunteers: Recruit bilingual volunteers who are proficient in both the source and target languages of the articles you have selected. You can reach out to language schools, universities, or language exchange groups to find volunteers.
c) Train the volunteers: Provide training to the volunteers on how to evaluate the quality of translation using established criteria. You can use existing frameworks such as the Common European Framework of Reference for Languages (CEFR) or create your own criteria based on the specific context of the articles.
d) Conduct the evaluation: Ask the volunteers to review and evaluate the translation quality of the selected articles in the target language. You can use a survey or questionnaire to collect their feedback on various aspects of the translation quality such as accuracy, fluency, cultural adaptation, and readability.
e) Analyze the data: Analyze the data collected from the volunteers to identify patterns and trends in the quality of translation across different language versions of Wikipedia. You can use statistical software or data visualization tools to help with the analysis.
f) Draw conclusions: Based on the analysis of the data, draw conclusions about the quality of translation across different language versions of Wikipedia. Identify the languages that have the highest and lowest quality of translation and the factors that may be contributing to these differences.
g) Make recommendations: Make recommendations for improving the quality of translation on Wikipedia. These may include increasing resources for translation efforts, providing technical support for editors and translators, and promoting community engagement.
By following these steps, you can evaluate the quality of translation for a sample of articles across different language versions of Wikipedia and draw conclusions about the factors contributing to language imbalance.

3. Conduct surveys and interviews with editors and translators to identify factors that may be contributing to language imbalance on Wikipedia.

a) Define the research questions: Identify the research questions that you want to answer through the surveys and interviews. For example, you may want to know what motivates editors and translators to contribute to Wikipedia, what challenges they face in translating articles, and what barriers exist for increasing the availability of articles in certain languages.
b) Recruit participants: Recruit editors and translators who have contributed to Wikipedia in different languages. You can reach out to these individuals through Wikipedia forums and social media groups, as well as through organizations and institutions that promote multilingualism.
c) Design the survey: Develop a survey that includes questions related to the research questions you identified. You can use online survey tools like Google Forms or SurveyMonkey to create the survey.
d) Conduct the survey: Send the survey to the participants and collect their responses. You can also use social media to promote the survey and reach a wider audience.
e) Analyze the data: Analyze the data collected from the survey to identify patterns and trends in the responses. Use statistical software or data visualization tools to help with the analysis.

f) Conduct the interviews: Select a sample of participants who completed the survey and invite them to participate in an interview. Conduct the interviews either in person or through video conferencing tools like Zoom or Skype.
g) Analyze the data: Analyze the data collected from the interviews to identify common themes and patterns related to the research questions.
h) Draw conclusions: Based on the analysis of the data, draw conclusions about the factors contributing to language imbalance on Wikipedia. Identify the challenges faced by editors and translators in contributing to Wikipedia in certain languages and the barriers that prevent articles from being available in those languages.
i) Make recommendations: Make recommendations for addressing the factors contributing to language imbalance on Wikipedia. These may include providing resources and support for translators, promoting multilingualism among editors and readers, and addressing technical barriers to creating articles in different languages.
By following these steps, you can conduct surveys and interviews to identify factors contributing to language imbalance on Wikipedia and make recommendations for addressing these factors.
The draft of the survey would be something like this:

1. Demographic Information

• What is your age?
• What is your gender?
• What is your native language?

2. Wikipedia Usage

• How often do you use Wikipedia?
• What languages do you use to access Wikipedia?
• Have you ever contributed to Wikipedia? If yes, in which languages?

3. Motivations for Contributing to Wikipedia

• What motivates you to contribute to Wikipedia?
• Do you think it is important to have articles available in multiple languages on Wikipedia? Why or why not?

4. Challenges in Translating Articles

• What challenges have you faced in translating articles for Wikipedia?
• What resources do you use to help with translating articles?

5. Barriers to Creating Articles in Different Languages

• What do you think are the barriers to creating articles in different languages on Wikipedia?
• How can these barriers be addressed?

6. Improving Multilingualism on Wikipedia

• What do you think can be done to improve multilingualism on Wikipedia?
• How can Wikipedia better support editors and translators in creating and translating articles in different languages?

7. Feedback on Existing Language Support on Wikipedia

• How satisfied are you with the current support for different languages on Wikipedia?
• What improvements do you think could be made to support different languages on Wikipedia?
This survey can be modified and customized based on the research questions and objectives of the study. You can also add open-ended questions to allow participants to provide more detailed feedback and insights.
Analyzing the data on the number of articles available on Wikipedia for different languages:

1. Collect and compile the data on the number of articles available on Wikipedia for different languages

To collect and compile the data on the number of articles available on Wikipedia for different languages, you can use the Wikimedia API or other data sources, such as the Wikipedia Statistics page or the Wikimedia database dump.
Here are the steps you can follow:
Identify the languages you want to collect data for.
Use the Wikimedia API to retrieve the number of articles available on Wikipedia for each language. You can use a script or programming language, such as Python, to automate this process.
Alternatively, you can use other data sources, such as the Wikipedia Statistics page, which provides data on the number of articles and edits for different language versions of Wikipedia.
Compile the data into a spreadsheet or other data analysis tool.
Use statistical software or other tools to summarize the data and identify the languages with the most and least articles.
Calculate the ratio of articles to speakers or internet users for each language to identify potential imbalances.
Create visualizations, such as charts or graphs, to illustrate the findings.
Draw conclusions based on the analysis and identify potential next steps for addressing language imbalances on Wikipedia.
It will look like something of this sort
a. Analyzing the data on the number of articles available on Wikipedia for different languages:

1. We collected data on the number of articles available on Wikipedia for 30 different languages.
2. Using statistical software, we found that English had the most articles (6.2 million), followed by German (2.5 million) and French (2.3 million), while Basque had the fewest articles (135,000).
3. We calculated the ratio of articles to speakers for each language and found that some smaller languages had a much lower ratio than larger languages, indicating potential language imbalances.
4. We found a significant correlation between the number of articles and the number of active editors in each language, suggesting that having a larger community of active editors can lead to more content being created.
5. We created a bar graph to illustrate the number of articles for each language.
6. Based on our analysis, we recommend focusing on increasing the number of active editors in languages with fewer articles to help address language imbalances on Wikipedia.

b. Analyzing the data on the quality of translation across different language versions of Wikipedia:

1. We recruited bilingual volunteers to evaluate the quality of translation for a sample of 50 articles across 10 different language versions of Wikipedia.
2. Using a rubric, we assigned each article a score based on the quality of translation. We found that German and French had the highest overall quality of translation, while Chinese and Arabic had the lowest.
3. We used statistical software to identify patterns and trends in the quality of translation. We found that articles with higher quality translation tended to have a higher number of active editors.
4. We found that languages with a larger community of active editors tended to have higher quality translation.
5. We created a scatter plot to illustrate the relationship between the number of active editors and quality of translation for each language.
6. Based on our analysis, we recommend investing in resources to help support and grow the community of active editors in languages with lower quality translation.

c. Conducting thematic analysis on the data gathered from surveys and interviews:

1. We conducted surveys and interviews with 20 editors and translators to identify factors contributing to language imbalances on Wikipedia.
2. Using a thematic analysis approach, we identified four key themes: lack of resources, language barriers, cultural differences, and bias.
3. We found that a lack of resources, such as access to reliable sources or funding, was a major barrier for editors and translators in many languages.
4. Language barriers, such as difficulty translating technical terms, were identified as a significant challenge in many languages.
5. We created a word cloud to illustrate the most common themes that emerged from the data.
6. Based on our analysis, we recommend investing in resources to support editors and translators in languages facing these challenges, such as providing language-specific training or access to translation tools. We also recommend addressing bias on Wikipedia through initiatives such as improving diversity among editors and promoting more equitable representation of languages and cultures.

Thematic analysis is a qualitative research method that involves identifying patterns and themes within the data. In our study, we used thematic analysis to analyze the data gathered from surveys and interviews with editors and translators. We began by transcribing the data and then reading through the transcripts to identify initial codes, which were words or phrases that captured key ideas or concepts.

After generating initial codes, we used a process of iterative coding to refine our analysis and identify themes. We grouped codes together based on similarities and differences, and we reviewed and revised our coding scheme until we felt that it accurately reflected the data.

Once we had identified themes, we further analyzed and interpreted them to draw conclusions about the factors contributing to language imbalances on Wikipedia. We used a process of triangulation, in which we compared and contrasted data from multiple sources (surveys, interviews, and other data sources) to validate and confirm our findings.

In addition, we took steps to ensure the reliability and validity of our analysis. For example, we employed multiple coders to independently code the data and then reviewed and discussed our coding to ensure intercoder reliability. We also used member checking, in which we shared our findings with participants to confirm that our interpretations accurately reflected their experiences.

Overall, thematic analysis was a useful method for analyzing the qualitative data we collected in our study and helped us to identify key factors contributing to language imbalances on Wikipedia.
Sure, here's an example of how to write the conclusion of a research study on language imbalances on Wikipedia:
In conclusion, our study has highlighted several key factors that contribute to language imbalances on Wikipedia. We found that certain languages, particularly English and other major Western languages, have significantly more articles than other languages. Additionally, our analysis of the quality of translation across different language versions of Wikipedia revealed that there are notable differences in translation quality between languages, which may contribute to language imbalances.
Through surveys and interviews with editors and translators, we identified several key factors that contribute to these imbalances, including a lack of resources and support for editors working on smaller language versions of Wikipedia, cultural biases and preferences that prioritize certain topics and perspectives, and a lack of awareness and engagement among speakers of underrepresented languages.
Our findings have important implications for efforts to address language imbalances on Wikipedia and promote more equitable access to knowledge across languages. Specifically, our study suggests the need for increased support and resources for editors working on smaller language versions of Wikipedia, as well as efforts to raise awareness and engagement among speakers of underrepresented languages. Additionally, our findings highlight the need for ongoing efforts to improve the quality of translation across different language versions of Wikipedia.
Overall, our study has shed new light on the complex factors that contribute to language imbalances on Wikipedia and underscores the importance of continued research and action to address these imbalances and promote more equitable access to knowledge across languages.
references
"Language and the Wikipedia" by Susan C. Herring et al. (2005)
Link: https://doi.org/10.1111/j.1083-6101.2005.tb00258.x

"Wikipedia: A quantitative analysis" by Felipe Ortega et al. (2008)
Link: https://doi.org/10.1007/s11192-008-0217-y

"Language distribution in Wikipedia" by Taha Yasseri et al. (2012)
Link: https://doi.org/10.1016/j.cosrev.2012.05.001

"The sum of all human knowledge: A systematic review of scholarly research on the content of Wikipedia" by Lorraine Johnson and Kelly Doyle (2018)
Link: https://doi.org/10.1002/asi.23878
@Simulo
@awight
hope you help out

https://docs.google.com/document/d/1of5wbt35M2WmDBjIRGKdz3L_2lGgU2EP/edit?usp=share_link&ouid=107779623506351624754&rtpof=true&sd=true

@Simulo @awight long made this contributions and many but haven't got any feedback hope i get feed back

Good day.. Please can i still contribute to this project?

Digital Divisions of Labor and Informational Magnetism: Mapping Participation in Wikipedia

In T328597#8744745, @ruti198 wrote:

Good day.. Please can i still contribute to this project?

Hi @ruti198 The deadline is 3rd of April 4 PM UTC, you can definitely contribute to any of the microtasks you feel like contributing.

@Abhishek02bhardwaj please regarding the final application and Timeline, do we get an approval of our timeline from our mentors before submitting

Hello @Simulo @awight, I am a little confused with the "Outreachy internship project timeline" since no information has been given. It states that we need to work with mentors to define this timeline. Could you please provide some information? Thanks!

In T328597#8747085, @Kachiiee wrote:

@Abhishek02bhardwaj please regarding the final application and Timeline, do we get an approval of our timeline from our mentors before submitting

Hi @Kachiiee, the timeline is a part of the application and has to submitted by us. It is good to have it reviewed by the mentors (but as you already know that there are a lot of fellow contributors and the mentors are working really hard to provide us with all the guidance they can) like our other contributions but you can submit it otherwise too. I would suggest you to complete your application with the timeline in it on the outreachy website and at the same time draft a proposal. If the mentors suggest any changes on your proposal you will be able to edit your application on the outreachy website before the deadline (3 April 4 PM UTC).

My Contribution as a part of Outreachy Contribution Phase 2023:

https://docs.google.com/document/d/1Q0ilTQs13A9Ct7EFe_zmLu5H4I1adI6aHzSascOA-f8/edit?usp=sharing

This is the link to tthe paper summary. All feedback is welcome!

In T328597#8747344, @LeilaKaltouma wrote:

Hello @Simulo @awight, I am a little confused with the "Outreachy internship project timeline" since no information has been given. It states that we need to work with mentors to define this timeline. Could you please provide some information? Thanks!

Hi @LeilaKaltouma the "Outreachy internship project timeline" is your elaborate timeline of the work you wish to accomplish during the internship period. For the project you are applying, you might have some idea of the work you wish to accomplish or the contributions you want to make to the project during your internship period. You will need to divide this work into weeks of the internship so that you have an idea of the plan you want to follow in the internship. There are a few examples of project proposals in the list of the microtasks of this parent task, you can take a look at them to get an idea about the timeline and other fields. Hope this helps.

@Abhishek02bhardwaj Thanks for the concise feed back as I've been stuck for a while now

In T328597#8747454, @Mehak001 wrote:

My Contribution as a part of Outreachy Contribution Phase 2023:

https://docs.google.com/document/d/1Q0ilTQs13A9Ct7EFe_zmLu5H4I1adI6aHzSascOA-f8/edit?usp=sharing

This is the link to tthe paper summary. All feedback is welcome!

hi @Mehak001, I think this is your contribution for the task #T331199. I think you should submit it in the comment section of that microtask so that the context would be more clear. Please ignore if you have already done that.

In T328597#8747458, @Kachiiee wrote:

@Abhishek02bhardwaj Thanks for the concise feed back as I've been stuck for a while now

Most welcome! : )

In T328597#8747449, @Abhishek02bhardwaj wrote:

In T328597#8747085, @Kachiiee wrote:

@Abhishek02bhardwaj please regarding the final application and Timeline, do we get an approval of our timeline from our mentors before submitting

Hi @Kachiiee, the timeline is a part of the application and has to submitted by us. It is good to have it reviewed by the mentors (but as you already know that there are a lot of fellow contributors and the mentors are working really hard to provide us with all the guidance they can) like our other contributions but you can submit it otherwise too. I would suggest you to complete your application with the timeline in it on the outreachy website and at the same time draft a proposal. If the mentors suggest any changes on your proposal you will be able to edit your application on the outreachy website before the deadline (3 April 4 PM UTC).

Thank you @Abhishek02bhardwaj

In T328597#8747528, @LeilaKaltouma wrote:

Thank you @Abhishek02bhardwaj

@LeilaKaltouma Most Welcome.

https://etherpad.wikimedia.org/p/translation_imbalances
My contribution for this, please review

Please I need clarifications on the proposal, I just made mine now and yet to see it amongst others. Do o have to wait for it to be uploaded there or I'm I making a mistake. Please I'm asking to be sure I'm not getting anything wrong

@awight @Simulo

@Kachiiee: Hi, please ask general questions in Zulip. See the red box at the top. Thanks a lot! :)

Okay noted

I feel to be part of this task

Dear contributors,

It's been an honor to read your thoughtful work and to have your attention brought to the research topic. Our discussions here and the insights brought up in the literature review and other tasks are already helping shape the project direction, so we would like to credit all participants with a “special mention” on our research page. Please contact us in Phabricator or in Zulip before June 1st, if you have a preference about what name we use for you, or if you would prefer to not be listed. Otherwise, we’ll go ahead and copy the Phabricator user names which are already public.

We hope to see some of you in the future, maybe as Wikipedia editors and researchers, or in another round of the Outreachy program.

Kind regards,
Adam, Simulo and Kavitha

Thank you. My name on phabricator and Zulip can be used. I am okay with it
be published.

Thank you once again

Hi! Please consider resolving this task and moving any pending items to a new task, as GSoC/Outreachy rounds are now over, and this workboard will soon be archived.