K (Kiki): Hi everyone, welcome back to Kartini Teknologi with Kiki and Galuh here. Today, we have a really exciting guest with us, and just like the previous episode we’re recording live so we’re sorry if you can hear some noises. Hopefully everything will be going well. Well anyway, Galuh, do you want to introduce us to our guest? Galuh is the one that suggests her to be our next guest. Coincidentally I’m in Jogja for a vacation, and Galuh is also here for a vacation, and turns out our guest is also in Jogja. So since we all can meet, we decided to record live today.

G (Galuh): So I was browsing Twitter the other day, and I saw Ligwina’s tweet about… I think it was women and skincare. And I was really happy to see the thread, at that time someone else was tweeting about, why do women care about skincare so much or something… make-up… and she replied with this empowering tweet, and we got to see women who could have everything—their skincare, makeup, hobbies, careers…

Z (Zahra): And they paid everything themselves…

G: And I came across our guest’s tweet. I think her profile is very cool—she’s a social researcher currently doing her PhD, and what stands out to me is that she also uses Python and R for her research. And I think it’s very cool, I really like seeing people in the intersection of technology and social sciences and other fields… it’s very interesting. So I thought that this would be a cool and interesting topic to talk about. And I think a lot of people, not just people working in the tech field but also in the social sciences field for example, are interested in hearing more about how we can utilize technology in our field. So maybe we can also explore that here.

K: So for our listeners who have a background in social sciences, maybe this can be inspiring to you all. So without further ado, let’s have our guest star to introduce herself further.

Z: I’m Zahra Amalia Syarifah, you can call me Zahra, it’s a lot easier, it’s a lot shorter, and I prefer it that way. I’m from Solo, but because my dad is from Lampung, if someone asks me where I’m from I would say that I’m from Lampung. But I was raised in Solo, I can speak Javanese, I can speak medok too [dialect]. But after high school I moved to the UK, attended university there, and after I graduated I continued my master’s in the US. And… I would call myself a sociologist. Why am I a sociologist? Because sociologists, we ask things that people are not supposed to ask, we ask things that people are taking for granted. And it’s really rewarding, when we ask questions that we didn’t think about, but then we get answers that make us go, “oh, so that’s it”. It’s fun. It’s a puzzle to crack, it’s a lot of fun.

K: Let’s start with your education. You told us that you went to school in the UK, maybe you can tell us more about your undergraduate studies, and then when you were studying for your master’s degree, and now you’re also doing your PhD as well, right? Can you tell us more about those?

Z: So I was the first child in the family, and my parents were always like, you have to be successful, you have to be someone your siblings can look up to. I wanted to attend a state university but I knew that I wasn’t good at math, I’m not the type of science student with stellar grades, and I’ve always preferred social sciencess anyway, like when I had to choose my [high school] major I chose social sciencess. When I graduated high school I remember my teacher saying, “Zah, you never got one math question right unless they have Rupiah signs in them.” So well… it means that I have a little basic in numbers, I just have to find something that pique my interest, and it turned out that my interest is in social sciencess, in sociology. At first I signed up for media and information studies, it was boring and I slept through the class. Since my parents wanted me to be successful, they told me to study business instead. I moved to business and… it seems like there was something missing there. I tried attending sociology classes, and in my first year I officially became a student of sociology and business management.

K: So it’s double major?

Z: Yes, double major… actually it’s one program, but I attended both sociology and business classes. So I was doing my parents’ demand in one hand, but on the other hand, [sociology] is my calling, that’s what I like. I also took politics classes in university, and my dissertation was finally about politics-sociology, sociological politics, discussing about political volunteers in Indonesia. It was done during the elections, where there were lots of discussions about buzzers, who buzzers actually are…

G: That was sort of like the beginning of… social media, was it… what year was it, during the election…

K: Jokowi’s election…

G: The first one?

Z: Yes, the first one. The methodology was ethnographic research, so I literally came, asked people, recorded them talking for hours, and then I transcribed them. During undergrad I didn’t touch numbers at all because I knew I’m bad with numbers. And then I wanted to continue studying, I continued in University of Chicago and I realized that if I didn’t take quanti at this point I’d never…

K: What’s quanti?

Z: Quantitative. So in researches there are two kinds of research—qualitative is more about words, meaning… in quantitative it’s more like statistics, numbers.

K: I see, so that’s how it started.

Z: Yes, so I kinda forced my way through it. I only had to take one methodology class during my master’s studies, but I was like, no no no, this is where I have to really try it, I have to learn from people. I mean I have to learn from people who are experts in network analysis, computational social sciences, machine learning, statistics… and within that one year I really had to fake it until I make it because my classmates were really smart, they already wrote their own Python library, and I was like… panicking, but well.

G: So were there specific classes for those or did you learn on your own?

Z: There were classes, but in classes we were given the bare minimum, like how you can continue learning on your own. So we can take classes, but in the end it’s up to you. I started from 0, so when it comes to coding it doesn’t matter if you have nothing at the start, you just need to be a hustler. Like, just push yourself through it. Fake it until you really can do it.

K: So you started learning coding when you were taking your master’s degree.

Z: Yes.

K: So what are you learning about now in your PhD?

Z: I’m in sociology now, so I’m taking PhD in sociology. I got an offer from University of California San Diego. In the statement when I applied I mentioned that I wanted to continue working in the intersection of computation and social sciences. And it turns out there was a lab for cognition language and computation, so I guess it’s meant to be.

G: It really suits your interest, right.

Z: In my old campus I was rejected, so it means… well, it means I’m not meant to be there, first. And secondly, well maybe this is going to be your new field, computation and social sciences.

K: When I read your LinkedIn profile, it seems like you have explored about mass political parties in Indonesia. Wasn’t it your dissertation for your master’s degree?

Z: Yes.

K: Can you tell us more about it, what did you do for your dissertation?

Z: So this is kind of exciting and… political. But to sum up everything, in the beginning of 2000s there were lots of Islamic mass organizations in Indonesia, but their tendency were more towards radical, hardline, and eventually leaning towards terrorism—remember, like the Bali Bombing, Marriott Bombing, that was really bad. The Indonesian government’s strategy to counter terrorism and radicalism was to work hand in hand with a particular Islamic mass organization in Indonesia. They were like, please lecture them so that they listen to you and won’t think about things like terrorism and jihad. So, this mass organization was asked by the government to reduce terrorism and others. This mass organization has a pattern of vigilantism, so they like doing things like sweeping, stuff like that. They like doing raids, so if they feel like the activity is amoral they would dismiss it. Yes, it’s radical from our perspective now… why would they let it happen? But if the choice is between terrorism and sweepings, of course the government would choose to have sweepings. It’s better to work with moralist thugs than terrorists. And finally, the Islamic organization would grow under the government, although its frontman was once in jail, and their actions had to be at the grassroot level, and well… their image was quite negative. But what’s quite interesting is that in the recent Jakarta gubernatorial election and the latest presidential election, the mass organization rose to the surface. And it’s not just the Islamic parties that worked with them hand in hand. What interested me was, why are parties with nationalistic, secular streaks would want to work with this mass organization. And then they would make an oration. This is something that’s like, wow, it’s a different pattern from how it used to be back then. This is where I use computation, so I use part-of-speech tagger, where I break texts into parts, so we know which one is the subject, which word is the adjective. Why? So that I can process a large amount of texts, because I sampled all news about this mass organization in Indonesia and all political parties in Indonesia, starting from 2008 to 2019.

G: So that’s 10 years.

Z: Yes… so there were about 30.000 news articles, so it would be impossible for me to process it qualitatively. So I used computation, I used Python, to find which adjective is the most representative of this mass organization in four elections in Indonesia. So two presidential elections and two gubernatorial elections in Jakarta. Why Jakarta? Because Jakarta is the capital city, so politics are represented significantly. And it turns out that the adjectives during those four elections don’t change. It’s always radical, violent, hardline, and antipluralistic. So those never changed. But what’s interesting is that there are changes in the verbs. So from 2008-2009 the closest verb to this organization is “attack”. So they liked attacking. They also liked to “disband”, so disbanding everything—events, assemblage… from 2011-2012 it was still the same. In 2013-2014 it was also still the same. What’s different in 2016 and 2017 is that there were less of such negative words. There were more neutral words instead, like “secure”, so securing events… securing something. “Summon”, summoning people… and “meeting”, meeting people. So this mass organization’s tactic within the past 10 years has changed drastically to practical politics that are usually sued by political parties. So it’s more…

K: Soft.

Z: It’s softer, and it intersects political parties’ activities more. Like gathering, negotiating. Though their adjectives haven’t changed, so people’s perception is still the same. They’re a hard organization, but that’s where the changes are.

G: So is it correct to conclude that, although their methods have changed, those haven’t successfully changed people’s perception about them?

Z: You can. But that’s politics, what works, what’s practical, what can be done. Like for example, if working with parties and working with other mass organizations can help them achieve their goal, why not right? Their political goal… I don’t want to say too much here, but if you want something, when it comes to practical politics, that’s what’s going to happen. We won’t see what’s their ideology, what they should be doing, and sometimes we’re confused about why is this party making a coalition with that party, right? Why is this mass organization with that mass organization, despite seemingly having different ideologies? In politics, ideology is one thing. Strategy is another thing.

K: So most importantly it’s about what is beneficial for them.

G: One thing that I notice is that, with the power of computation, coding… you can explore topics that you couldn’t have touched before because let’s say, it’s difficult to interview each person, practically impossible, especially when the topic is quite sensitive like this… it can be difficult to find people to interview… and I like to hear that with coding, with Python, with POS tagger let’s say, we can obtain all of these information without having to interview each person.

Z: And what’s exciting in social sciences is that, we have a question, right? So how can we answer that question with a constraint in resource and funding? Because when I was doing my thesis, I did it under a year and I didn’t get a huge funding, and I was like how can I touch this problem without having to go to Indonesia, how can I still understand this. And at the end, well, computation is my savior.

K: So we’ve talked about data, now let’s shift a bit to coding. So you started learning Python and R when you were doing your master’s, right. So… your background is from social sciences, how did you learn to code, like did you learn right before you were doing your thesis, or… what’s the history?

Z: So at the start I felt like this university is good in computational social sciences, because they have a lab where social scientists work with computer engineers. So I decided to learn it, whether I’ll use it for my thesis or not that’s another story, I’ll learn it first. In the first quarter I took an R class, second quarter I took a Python class, and I wrote my thesis on the third quarter. So… I was probably kind of reckless, my friends have literally spent years coding, and I just decided to go for it like this. My lecturer told me, “Zah, you cannot code. You’re not the best hacker, but you’re a hustler.” So you can force yourself to be able to do it, which is fine by me. But I didn’t sleep for days, like before the deadline I stayed up until 4 and slept at 6, worked again, from 9 to 12. At 12 I submitted it right away. I really forced it but it was worth it.

K: So the materials were given in your classes?

Z: For R they taught us the basic codes, for Python it was a computational social sciences class. My classmate worked with my lecturer to write a Python package. If you want to try it, it’s called lucem_illud, it’s for sociology and content analysis. And we applied it in class. Of course, we can write our own code, develop it on our own, like for example I was making a network analysis and it wasn’t part of the class. So I had to adapt, I had to come during office hours because I couldn’t understand it all by myself.

K: So you also learned from other sources, right?

Z: Yes.

K: Where did you learn it all from? Video tutorials, or…

G: Or Coursera…

Z: My university was very accommodating, so I got a free Coursera subscription while I was a student there. So I used that. There are also many free resources as well, like Coursera, and I like watching Khan Academy since my basics in mathematics isn’t that good. So I had to learn linear algebra, matrix algebra…

G: The course is very good though, I also learned from there.

Z: Right?

G: It’s super cool. I learned calculus, linear algebra from Khan Academy.

Z: That’s right. And they explained it with colors, so I become more confident with it. But yeah, the basics… you need to know statistics and mathematics and Khan Academy really helps.

G: It’s so good, I approve.

Z: Don’t be embarrassed if you don’t know something.

K: Galuh and Zahra approved.

G: I’m curious, when people are learning to code there are tons to learn about. Like… there are so many programming languages for example. Do you have any suggestions for our listeners with a background in social sciencess, like if they want to learn coding, where do they start? Especially what things are mostly useful for applied social sciencess.

Z: Actually it depends on what you want to do. If you want statistics and don’t want to learn programming, you can do it with Stata or SPSS. But if you want great visualizations, R is usually really good because there are many resources. If you use the hashtag R in Twitter, there are many communities that you can find. There is R ladies, a community of women who use R, and most of them are professors or researchers. So if you’re a social sciences researcher, you want to create map projections or cute graphs, most likely someone has developed the package if you don’t want to develop it yourself. And eventually if you read other people’s code, you can develop the code on your own. However if you want to do a more qualitative research, I think you better use Python, because Python… maybe I’m biased because when I learned qualitative I used Python. You can do it with R to actually, but Python… I don’t know, is “more serious” in terms of the computer engineering, so engineering people, math… they use Python, and when they intersect with social sciencess there are a lot more materials available there. The machine learning packages I think are also better in Python. We can do supervised learning, unsupervised learning, which is in line with social sciences. If we use unsupervised learning for example, we use topic modeling, we can dump so many documents and see what the patterns are like. And then we can analyze, oh, this is this group, this is that group, then we synthesize the meaning socially. In supervised learning, we start from theories, especially in social sciencess whether it’s politics, economics, psychology, or like myself sociology. We can insert certain codes for several social phenomenon that we find in the texts, and then we can have our computers run it. This thing is for lazy people, and I’m a lazy person.

K: But technology is made to make those things more efficient, right. And you mentioned that you used data from the news. Can you also use data from the social media, or where else do you usually get your data from?

Z: When I evaluated my research, I realized that my research is biased because I only obtained news from English-speaking media. This means that I excluded many Indonesian media which might have a certain political tendency. One of the problems is that, I was running out of time, I didn’t have the money to ask 10 people to help me code, and in terms of language Indonesia is considered as a low-resource language. There are a lot of English, Spanish, Mandarin packages. And because I still didn’t know a lot, I also didn’t have much time, I used news written in English. So I scraped several Indonesian and foreign media, my computer was running for one semester.

G: You scraped a lot of news right, about 30.000 of them.

Z: And I wasn’t that good in coding yet, so for the first trial I waited for an entire night and it turns out I got the wrong result, or the result was not like what I expected it to be.

G: We’ve all been there right, waiting for an entire night and suddenly there’s an error that we haven’t caught. Aside of news, where else do you get your data from?

Z: We can get it from social media if we created an API, we asked Twitter to “call the data”. My friend scraped Twitter and they created an analysis regarding how hoaxes spread, so it’s possible. We learned coding together and we ended up doing different things. The point is, start somewhere, you go anywhere you want.

G: Can you tell us, say if you want to do some research, what are the steps? From gathering data to, you know, the analysis is finally completed.

Z: Maybe because I’m a social scientist, I start from questions about my environment. For example, what’s the correlation between unemployment and inflation? For such problems the data is usually good. The US’ labor statistics is complete, and data about inflation from University of Michigan is also complete. So that’s pretty comfortable, but it’s usually statistics, and I’m honestly not… I’m not a big fan of like, pure statistics, well everyone has their cup of tea. I’m more into texts, observing social phenomenons, reading the theories, and then I see the gap in the literatures, and after I know what I want to look for, I’ll use supervised learning, so I already know what I want to look for in our data. If we don’t know yet what we’re looking for we usually use unsupervised learning. But in research we usually already know a) the question, b) how the data is like. Many people have research questions and arguments but they are not in line with the data, or are not in line with the conclusion. That’s the homework of social scientists, making stories, building arguments from so many data.

G: I’m also curious, what libraries do you use for your research? Python or R libraries that you use the most?

Z: For R I usually use ggplot, dplyr.

G: What are those for?

Z: To make beautiful graphs. I like graphic design, but stupidly during my undergraduate I didn’t create beautiful projections using Excel and others. I wanted to make beautiful ones and I used visual design softwares which is stupid because it’s difficult and inaccurate.

G: Because you have to adjust it according to the numbers and the proportions.

Z: And I was fed up with Excel’s pretty basic projections, so I looked for packages that I can use. Turns out R has them. And I also like reading BBC, and BBC usually has these projections about proportions of people in the parliament… they have these circles with colors that can change, or maps… like maps about poverty in Indonesia. And we also can create these maps per region. So my orientation is not really about processing the data, which is probably not right. But everyone has their own drive, right. I use R because I want to create a presentation that people enjoy looking at.

G: But that’s also important, right? If we already have all of these numbers but people cannot understand them because the presentation is ugly or too difficult to understand, that’s no use, right? The goal is to make people like us understand the data.

Z: Yes, especially if you’re looking at econometrics, and they have this huge statistics table. We can understand it of course, but we have to read it several times. If we have graphs, it’s easier to communicate them to people, and I’m not the kind of person who wants to be a scholar who stays in my ivory tower, like only writing for scholars, that’s not what I want. I want what I know to be communicated to other people, it’s much more exciting.

G: You said that you didn’t use news written in Indonesia because it’s difficult, for example there are not many libraries for the Indonesian language. Are there other challenges, like for example it’s still difficult to use open data in Indonesia, are there other constraints that make it difficult for us to do computational research using Indonesian data?

Z: It’s a lot of homework, yes… for example in Python, if we want to do machine learning or natural language processing, there are a lot of packages like gensim and others. However, the research centers are usually in the US, like Stanford which is a pretty huge one, or UW Madison which is currently on the rise in terms of computational social sciences. Well… at the end it becomes more biased, because we run data based on different languages. At the end I took the initiative to seek for resources for the Indonesian language. I heard that there were a few people in ITB, but until this point I haven’t met them yet at all. There are also people practicing natural language processing in the industry, but their concern is usually not to help academic research right, we do it for the money. It’s kind of difficult. Maybe when I’m doing my PhD, it’s going to take quite a long time right, so maybe I’ll have time to really do it on my own and create something that is open source. I don’t know… it will take time but it should be worth it.

G: The impact must be huge though. That’s one of the things I often hear, like for example NLP for the Indonesian language is difficult.

Z: Our second guest, Nilta, also did NLP and she said that resources for the Indonesian language is quite limited.

G: And open data in the US is really good, while here… I was going to use it for something, but it’s still quite messy, not as good as other countries’ open data so it’s quite challenging.

Z: If we want to look at the constitution for example, it’s all scanned, but you know that sometimes the scans are not that good. If you want to use optical recognition…

G: There can be mistakes there.

K: There can be an incorrect transfer of information.

Z: For statistics… it’s also not that good, say that you want to play with numbers. BPS is also quite difficult if you want to ask for data. However it’s good that Indonesian researchers are starting to collaborate with other foreign researchers, like for example Australian National university is pretty close to UI or UGM. They also have datasets specifics for Indonesia. Or World Bank, one of the researchers is in Chicago, I know them, and they created this database about violence in Indonesia. So there are quite a lot of them. However, I’m pretty worried about the law that will arrange researches in Indonesia.

G & K: Spill, spill.

Z: It can really ruin my mood talking about this. So it says that if foreigners want to come to Indonesia to conduct research, they have to have this permit.

K: So it’s like a visa?

Z: Well it’s better if it’s a visa… but in this case they have to write this proposal, the proposal will be discussed… well it can be a double-edged sword; in one way this can protect Indonesian researchers who are working with foreign researchers to ensure that, yes, there will be a transfer of knowledge, this will be fair and ethical… but on the other hand the bureaucracy is slow, and I’m more concerned about censorship actually.

G: Because someone has to say yes/no to it, right.

K: So it’s not going to be neutral anymore.

Z: It’s just like how it is in Hungary. In Hungary they have the Academy of Sciences, so it’s like Indonesia’s LIPI (Indonesian Institute of Sciences) right. Now their administration is now under the ministry of research. So all funding that the academy will give must be approved by the government. The government is an authoritarian one. I don’t want that at one point Indonesia will be like that. I can’t say whether Indonesia will slide back to authoritarianism, but for sure, it’s not a liberal democracy. Even they continue perpetuating censorship practices. Or like, the law enforcement is still difficult. I’m afraid that at one point, this can threaten freedom of opinion, freedom in academia, exchanging ideas. As simple as this: for example, there is an earthquake or tsunami in Indonesia. Say that there is a researcher from Australia who wants to come to do research on the tsunami. They have to submit their proposal and it will take months… the phenomenon is gone.

G: Or maybe not relevant anymore.

Z: Well yeah, I’m pissed off, but what else can we do.

K: It’s like what Cinta says, “basi! Madingnya udah terbit.”

G: Have they approved the law or is it still a bill?

Z: It was just a bill, but suddenly it’s now part of the law… I haven’t checked the latest update, last time I checked it’s now the law, but I haven’t read more about it because I’m pissed off. I’m lucky that I’m Indonesian, but at the same time if my collaborator is foreign…

K: Does this law still apply if the foreign researcher is collaborating with Indonesian researcher?

Z: If the researcher wants to go to in Indonesia, then yes. I haven’t read the bill fully, I was just skimming through it so maybe I’m getting some things wrong. I acknowledge that I don’t read it, because there was a lot to read and I’m pissed off already so yeah. But that’s the gist of it. Ask people studying law about this, I can’t speak a lot about this, but there is frustration. Fear. Worry. I mean… my research is not sensitive, but there are people who want to do research on, say, ‘65. That’s sensitive right, it’s going to be more difficult for them.

G: It’s terrible if they ended up passing the bill.

K: It wasn’t the law actually, just a regulation, so it was just… okay. And then I think it was the Minister of Home Affairs, they got protests, withdrew it, canceled it, and now it’s a bill. And the latest update says they passed the bill but I have to confirm once more, I cannot be mad I have to read it first. It’s my mistake, I should have read it with a cool head.

G: Are there other challenges that you have faced so far, outside of data or research about Indonesia in general?

K: Or maybe challenges when learning to code?

G: And how did you solve it?

Z: My family’s background is not really academia, they do business, so they supported me to go to university but it was kind of difficult to gain their support for me continuing my PhD. Parents are usually like, why do you have to take years to go to school. So actually, support from people close to you is really important. But if you like one thing… sometimes you just get drowned in it, you just really like it. I don’t wanna say that liking something enough will be enough, because honestly you’ll need a mentor. And I’m lucky because I get a mentor that… my lecturer is very patient. They understand that I don’t understand. They would tell me. But they weren’t the type who would dictate me what to do from A to Z, they would give me directions instead. They wouldn’t tell me where to go, but instead they would tell me, if you want to go to Jakarta, you can take this highway. You can take a flight. You can also take the train. It’s up to you. If you’re capable of taking the train, then do it. At that time, if I use the analogy of going to Jakarta, I think I was walking because I was very slow. Very slow. But it was rewarding, because I read my lecturer’s reference letter for an application, and they said, “Zahra starts with a zero ability in coding in this class. But her project came out as, if not, one of the strongest in the class.” Perseverance is like… there are so many friends who would discuss with me, and they were like “this is so difficult, let’s switch projects” and I didn’t want that. I really wanted to know, I really wanted to apply this to my thesis. So my final project in the computational class was in line with my thesis, and I was like no no no, I have to do this. But it pays off. I was kind of bleeding throughout, I didn’t turn off my computer, I didn’t sleep, but I had fun.

G: Okay, one more. What are your future plans, or future projects?

Z: I really want to become a lecturer. I really want to. Now I’m at UGM, helping out the Center for Southeast Asian Social Studies at UGM, reviewing papers, book manuscripts. It’s fun, observing people’s arguments, how someone develops an idea… it’s something interesting for me. When I become a lecturer, I want to be like that. I want to see how each person develops their idea. Because honestly, when I went to school in Indonesia, every time I asked something the answer was usually something along the line, “because of this, then this. This is because of that. Don’t ask any more question.” I want to become someone who’s like, “what do you think? What do you think this phenomenon is like?” It’s not a matter of right or wrong answers, it’s more like, how do you think? It’s fun to delve into other people’s mind. It’s fun to delve into things. That’s it.

K: Hopefully it all works out for you. Last but not least, any messages for our listeners? Either about social sciencess, learning to code, or general messages.

Z: In general… do the things that you like. If it’s hard, it will be the fun kind of hard. And most importantly, my life motto is, fake it til you make it. Despite the fact that we’re not that good at something, just ask. And keep hustling, it’s no problem.

K: That’s so cool. I honestly am very inspired hearing Zahra’s story. She comes from a different background, even with zero knowledge on coding, and her classes only taught her the basics, but she managed to apply all these for her research, I think that’s very cool. All right, so I hope this episode inspires you, and that’s all from us. See you on the next episode!