Hi, everyone see. I am a research, a staff member at IBM Research and today I'm very excited of presenting the research paper mobilizing social media data reflections of a researcher mediating between data and organization, which is part.
Of my doctoral research, um, presenting this work on behalf of my co-authors Marisol Villacres, Milagros Miceli, Benjamin Hernandez, and
[...] and Christopher [...]. My former advisor. During the last decade, various actors in the field of humanitarian action have proposed analysis of social media data as a promising pathway for nonprofit organizations. There are many factors that have lead organizations
to rush into this option by conveying a sense of being abundant openly available and entailing at a lot of different experiences and opinions social media data tends to be portrayed as an efficient and effective solution to inform organization's operations for first knowing
how to deploy the resources and reporting impact back to founders. However, scholars within critical Data studies and STS have issue warnings about using social media data to inform interventions that affect communities due to the particularity of these type of data, including limited
representation within data sets this type of data cannot guarantee that the perspectives and needs it highlights are representative of those who need support retaining context. This refers to the difficulty of maintaining the context of social media data when we're using it outside of its place of production. Such
Characteristics of social media data complicate how organizations in the humanitarian context can extract actionable insights from this data considering that to be used in social media data needs to be mobilized and what I mean with mobilized is moving user generated content from its place of origin the social media platform into a different context.
Now, despite the limitations of social media data founders, researchers and other decision making actors continue to champion computational techniques to analyze social media data for informing humanitarian action. Therefore, it is critical to better understand how nonprofit organizations.
doing humanitarian work engage with the process of analyzing social media data to make effective valuable decisions on the ground. We respond to this need by exploring how the culture of objectivity of our partner organization and our commitment to approaching data from a community perspective shaped the process.
Of defining negotiating and interpreting data, including ground truth data to inform future interventions. This research took place at the beginning of two thousand and twenty- in Mexico in Mexico City when the country was on its highest alert level due to the pandemic of COVID-19, I conduct the research while I was interning with the accelerator lab in Mexico.
My home country and the Accelerator Lab belongs to the accelerator Lab network of the United Nations Development Program, the UNDP which is the United Nations lead Agency or International Development in May two thousand and twenty- the accelerator lab launch the project COVID-19 Social inventory.
As part of the overall pandemic response, the project consisted of identifying the existing capacities across communities in Mexico City that good support responses to the pandemic, so that in the team focus on identifying and analyzing citizen led initiatives already responding to the crisis.
We decide to explore the data as an option to identify citizen- led initiatives. So in my role as an intern, I was in charge of mediating exploration in this paper. Um, we reflect on the process that accelerated lab experience to decide on the use of social media data.
To collectively create grown through data and negotiator, meaning including the limitations and counter. No, what is unique from this study is that we report from my perspective as a mediator between the organization and the data and our motivation for conducting this investigation is to show the decisions negotiations and tradeoffs in both.
In analyzing different races that heavily influenced the conclusions that can be drawn from social media data. So this investigation is a practitioner research project in which we use, send me the graphic methods such as participant observations, reflexive first personal accounts, and the analysis of text documents.
Especially fill notes and memos we report on nine months of remote field work in which I interned with the accelerator lab and in total, my engagement comprised around five hundred hours in which [...] decelerated lab in various capacities as a result of our reflexive analysis.
Is within the five four key moments from the project. These moments are defining the data set defining ground truth, making sense of data and extracting value of data and communicating insights.
These moments of negotiating of negotiation defined the process of mobilizing social media data and the insights we extract from the data, the moments we highlight in our paper are common in any data science project. However, what we describe in our paper is how the decisions of each of those moments were informed by.
The goals and capabilities of the accelerator club, as well as on the ground knowledge and position nullity of the researcher mediate in between the organization and data, which in this case was me new time constraints, I will not be able to go into detail about each of these moments, but I would like to encourage you to review the paper.
Building on our analysis, we unpack three assumptions that researchers using computational techniques to promote the use of social media data in non- profit organizations might face throughout their journey. The first assumption is that the use of social media data is straightforward fast and cost- effective hour and.
Always provides and breakout evidence that extracting value from social media data is not a quick nor cost- effective solution.
The obstruction of value from social media data demands, at least three types of resources from nonprofits, organizations, time, flexibility and freedom. So practitioners need to ask themselves and organization the following questions, what human resources does utilization have what level of pressure to act in.
Organization facing and what explanation spaces can eat for the second assumption is that the objective findings are the main value that social media provides for nonprofit organizations working in your monitoring context valuable results results from the notification, Intel as.
[...] for deciding when, and where to act in this project, the value lies in the narratives that I, as a mediator present, which reveal other actors and dimensions of the examiner, the problem that accelerator laugh hadn't considered before, for organizations that delivered humanitarian relief, integrating social media data.
And into their work entails recognizing the data along cannot fully reflect conditions on the ground instead. Organization should approach user generated content as a starting point that needs to be completed with additional information using other sources of data and methods to that end. It becomes important for the.
Data expert to continuously ask what are the concepts frameworks and beliefs about human behavior that the organization has, and what are the types of decisions that organization plans to inform through social media data analysis. The third assumption is that the effectiveness of the data export work lies in the computational methods, they use.
However, our finding show that we need to consider the context or the data is generated as part of the data analysis. This can help bring a more meaningful and responsible interpretation and use of data in this sense, it is critical that data experts continuously reflect on their [...] and how it affects their data analysis.
Abilities and decisions. So researchers engaging immediate in social media data work need to ask themselves what potential negative effects do. I foresee introducing social media practices to the organization and what is my responsibility in the way the organization perceives the potential of social media.
To summarize the contribution of this research is first, then critical evidence of the limitations that intel integrating social media data into the work of nonprofit organizations and second the questions we propose to data experts to promote reflection in identifying and facing the limitations of this type of data.