## 4 Results and Discussion  
We tested the above approach by developing a structural ABM of household food security using semi-structured field interviews, for example, the excerpt in Figure 2. Our qualitative data contain 42 semi-structured interviews from different members (young and old, male and female) of farming households in Koutiala, Southern Mali. The interviews were initially conducted to develop mental models of household food security in the region [70]. Verbal consent was obtained from the participants prior to the interviews. The interviews were originally conducted in the local Bambara dialect and then translated into English for model development. The mental model development followed the lengthy conventional qualitative data analysis approach that used multiple coders and keyword-based sentence extraction. That inspired the research team to develop a more efficient alternative data processing and extraction approach for ABM development, presented here. First, we grouped the interviews by the member types (i.e., elder male, younger male, elder female, and younger female) and analyzed the grouped narratives collectively. After preprocessing the interviews using NLTK tools, we used the scikit-learn Tfidf Vectorizer to reduce the volume of qualitative data. Textacy was primarily used for identifying candidate agents, actions, and attributes. Additionally, textacy extract (textacy.extract. semi-structured statements) was used in converting sentences to structured outputs. Finally, we manually filtered the unsupervised outputs based on their domain relevancy and ambiguity. The final outputs were then visualized and conceptualized using Gephi ([[https://gephi.org/](https://gephi.org/)]([https://gephi.org/](https://gephi.org/))) (accessed on 18 May 2020) and Lucid Chart ([[https://www.lucidchart.com/](https://www.lucidchart.com/)]([https://www.lucidchart.com/](https://www.lucidchart.com/))) (accessed on 21 May 2020) platforms (Figure 3). **Enumerator:** When the production reaches home, how do you consume it? **Surveyed:** First of all, we are 48 people in my household. After harvesting, we beat and weigh the crops. Then, we pick the quantity of food that is needed to feed the household. That quantity is given to women for cooking. We continue with that quantity until the new crop is harvested. When food is cooked and ready for eating, it is distributed by a plate to five and six persons who eat together. As the daily food consumption is known, we know what quantity we can sell to address household needs. You know, when crops are harvested, we tie them. Then we pick some pieces for beating. After beating, we weigh and stock. Then, we know the existing quantity in the store. If it is maize, for example, we have a cart and beating machine. We take one load of maize in the cart. Then we beat and weigh it and finally stock in the store. Farmers start beating crops and stock them. Because, a researcher like you, **[PERSON] of Sikasso and CMDT** trained us on post-harvest management. By following lessons learned from training, our food won't be over. Even if it happens that our food finishes, we would know what food to buy without any difficulties. With lessons acquired, we can produce and increase our production that will feed all our household over the year. Unless our food is stolen, it will cover for the year. **Enumerator:** What are the main crops you are producing? **Surveyed:** We produce maize, sorghum, millet, and cowpea in one hand and use the same crops to feed ourselves on the other hand. Some farmers prefer feeding themselves with millet all over the year. Even if they produce maize, they sell it. Although other farmers prefer maize, we consume all the crops we produce. We may consume one crop in one month and shift to another for another month. This is how we shift food consumption. **Enumerator:** Who decides to shift from one food to another? **Surveyed:** It depends. Some crops are easier to process than others.