PhD Candidate at Boston University / UX Researcher at ...Data-driven research that relies on...
Transcript of PhD Candidate at Boston University / UX Researcher at ...Data-driven research that relies on...
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Social Science Librarians Boot Camp 2019
Brittany Andersen
PhD Candidate at Boston University / UX Researcher at Ancestry
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1. Introduction to Social Networks
2. Data Collection Methods and Limitations
3. Overview of Social Listening
4. Live Demonstration of Crimson Hexagon (Paid Platform)
5. Q&A
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● What is a network?○ A group or system of interconnected
people or things.
● What is social network?○ Social structure made up of
interconnected people specifically. Emphasis on interactions.
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● Community● Organizational● Interest groups (health, music,
politics, activism)● Familial● Professional
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● Social media seems to intersect with nearly every aspect of personal and public life in contemporary society.
● Platforms are not discipline specific (like other methods such as ethnographies, surveys, etc.)
● Data-driven research that relies on analyses of social media data has grown tremendously in volume and rigor.
● Why: This data provide access to what people do, not what they report to have done (in terms of behaviors, content, engagement, sentiment).
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● Staying up to date on new developments and events in a field (such as health/political) or social circle.
● Gain insight into how information (or misinformation) spreads
● Understanding hierarchy and influence in social settings or fields.
● Building strategic connections important in any job field or enterprise.
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● Not all phenomena will resonate as much on social media – (many things still happen elsewhere).
● Understanding social media depends on data, which can be incomplete and/or expensive.
● Platforms are different and may require varying approaches or tools, think “medium specificity.”
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● While we can use these methods for hypothesis testing, we are currently undertaking exploratory data analysis. ○ We don’t know what we will find!
● We need methodological flexibility.○ Adjusting keyword searches, filtering out terms, consideration of other tools
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● Which users are talking?○ (Who are they, what do they do)
● Where are the users from?○ (Country of origin/geolocation)
● What are they talking about?○ (Politics, health topic, world events)
● When are they talking about it?○ Timeframe, spikes in dataset
● How are they talking about it?○ (Sentiment, tone, writing style,
grammar versus chat speak)● Characteristics of conversation?
○ (Retweets, link sharing, @mentioning specific users, hashtags associated with topic)
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● In social media monitoring, we mostly rely on Twitter data due to widespread accessibility.
● Limitations due to accounts with more privacy restrictions.○ Collection from Facebook pages than personal accounts.
● Collection for research is typically through the source (e.g. Twitter), via third-party, or even hand-collected
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Twitter Search (Free)
● Free● Data comes in near-real-time● No access to historical data or
visualization options● Limitations on queries
○ Basic keywords, limited filters● Requires you to think and plan ahead
○ Like a radio, you cannot replay a song that has already played
Twitter & Third Party (Premium)
● Expensive● Twitter Search (Premium/Enterprise)● Third-party site (Sysomos, Crimson
Hexagon)● Access to historical data +
visualization options (third-party)● More flexibility with research queries
○ Advanced Boolean strings and search filters
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● The process of monitoring and tracking digital social conversations● Widely-used platforms: Sysomos and Crimson Hexagon
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● Analyzing users○ Who is partaking in discussion?○ Who are the influencers?○ Demographics
● Identifying popular content○ What is being shared?○ Links, retweets, original comments?
● Topics of interest○ Public health -> antimicrobial
resistance○ Chronic pain -> depression
● Post volume○ Spikes in conversation?
● Media○ Videos or photos shared
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Brittany Andersen
PhD Candidate at Boston University / UX Researcher at Ancestry
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