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BibleTech 2019

January 11th, 2019

If you’re reading this blog, then you’re probably interested in attending the BibleTech conference, held on April 11-12, 2019, in Seattle.

You may even be interested in submitting a proposal for a talk; if so, the deadline is January 31.

Here’s what I plan to talk about if they accept me:

Designing for Agency in Bible Study

This talk explores the theory and practice of designing a Bible study experience so that the distinctive property of digital media–interactivity at scale–enhances rather than constrains the participant’s agency, or ability to act. We’ll discuss how people’s psychological needs for competence, relatedness, and autonomy affect their approach to and expectations of the Bible and church life, and how developers can support these needs by considering agency during the design process. We’ll also look at a specific application that HarperCollins Christian Publishing has developed to put these ideas into practice and promote agency in the context of daily Bible reading, explaining how and why we transformed a product that wasn’t a good fit for print into one that feels digitally native.

Using 3D Software to Enhance the Resolution of Bible Maps

December 28th, 2018

The problem with using satellite photos for Bible (or other historical) maps lies in their photographic nature–they present the world as it is, with modern cities, agriculture, land use, and other infrastructure that didn’t exist in the ancient period that the maps are depicting. However, satellite maps are useful in showing “true-color” views and revealing features like transitions from deserts to wetlands.

If you’re not using satellite photos for the Bible maps you’re creating, you’re using other data, like elevation; indeed, with only elevation data, you can produce a variety of map styles. Shaded relief shows hills in a naturalistic way, approximating the look of satellite images. A hypsometric map, where the map color changes with elevation, also depicts this data, though I would argue that hypsometric maps can be misleading if they transition from green colors at low elevations to brown colors at higher elevations, since people have become used to satellite photos with these colors as depicting land cover.

The main problem with relying on elevation data (a digital elevation model, or DEM) is its relatively low resolution; until 2015, a 90-meter resolution (i.e., one pixel of elevation data corresponds to an approximate square 90 meters by 90 meters) was the highest resolution freely available worldwide (well, mostly worldwide). In 2015, the SRTM worldwide elevation data became available at a 30-meter resolution, or 9 times higher resolution than previously. Also in 2015, similar ALOS 30-meter data became available. If you’re willing to pay tens or hundreds of thousands of dollars, you can also find proprietary elevation data at resolutions of 5 meters. Most of us aren’t in a position to pay that kind of money, however, so I’m interested in free data.

Bible atlases produced before 2015 almost certainly use the coarser 90-meter resolution, while Bible atlases produced since (though as of late 2018 I’m not aware of any) would likely use the 30-meter resolution and can zoom in much further without becoming blurry.

However, 30 meters feels rough compared to the satellite imagery available in Google Maps, which is often at 30 centimeters. Even free imagery from the European Sentinel-2 project is available at 10 meters, or 9 times higher resolution than 30 meters.

DEM Enhancements

The question I have is whether it’s possible to enhance a 30-meter DEM to bring it closer to the high resolution that Google Maps is training us to expect on maps everywhere.

To answer that question, I turned to Terragen, 3D modeling software designed to render photorealistic landscapes. (I actually tried several different programs, but Terragen was the least confusing.) Terragen and similar programs procedurally improve resolution by adding fractal enhancement–in other words, they extrapolate from the available data to add plausible, if fake, detail. My process was the following:

  1. Find a high-resolution DEM to use as a reference for the output of the process.
  2. Downsample the DEM to 30-meter resolution to match the DEM available worldwide.
  3. Enhance and style the DEM in Terragen to mimic a satellite photo.
  4. Compare the output.

The U.S. Geological Survey has started making elevation data available at a 1-meter resolution for select parts of the United States. I picked a desert area near Dayton, Nevada, that roughly matches the terrain of ancient Israel (since Israel will probably be the subject of most Bible maps).

I converted the USGS .img file into a geotiff using gdal_translate and resampled it to 30-meter resolution using gdalwarp -tr 30 30 USGS_NED_one_meter_x27y436_NV_Reno_Carson_QL2_2017_IMG_2018.img nv-30.tif.

The result was two tiffs that I imported into Terragen. After that, I spent some time coloring and styling them, with the below results:

Comparison of six different views of the same scene.

This image shows 1-meter shaded relief, 30-meter shaded relief with blurry bicubic resampling, 10-meter publicly available satellite photo that I slightly retouched, 1-meter colored and enhanced in Terragen, 30-meter colored and enhanced in Terragen, and the Google Maps view for this area.

I feel like the 30-meter Terragen view, which is what you could plausibly produce for Bible maps, looks pretty OK, actually–though a trained 3D artist would do better. The 1-meter data, while accurate, reproduces modern features like the road on the right side, which is unhelpful for Bible maps–mitigating modern features is the one of the main points of this exercise. While the 30-meter view doesn’t have all the detail of the 1-meter version, the rendering feels plausible to me.

Of course, “plausible” doesn’t mean “accurate,” and there’s the question of whether it’s ethical to enhance terrain in this way–you’re essentially inventing detail that doesn’t exist in the source data, which could mislead someone if they believe that the detail reflects reality. It depends how far you want to push the idea that all maps are in some way plausible fictions.

Scaling Up

What’s needed to implement this technique in production?

  1. A base map to use for coloring (I’d use Natural Earth II–I tried it in the Nevada scene and think it could work–but you could also use satellite imagery or your own colors).
  2. A way to export and reproject the finished product. My free version of Terragen can only export images 800 pixels wide; you’ll probably want to export them at over 10,000 pixels wide. And then you’ll need to stitch them together and reproject them to Web Mercator to display them in online mapping applications.
  3. A way to layer the images with other data (such as bodies of water and labels).
  4. A delivery mechanism (probably tiles over the Internet, as with Google Maps and most mapping applications).

Conclusion

This approach represents a plausible way to improve the resolution of Bible maps or other historical maps using only publicly available, free data. Although it creates some ethical problems, with proper disclosure it could potentially be a useful way to make Bible maps more compelling and zoomable.

Art of the Bible

November 8th, 2018

Art of the Bible is a website I made to catalog 5,800 freely available historical Christian-themed artworks on Wikipedia. The site primarily focuses on European paintings from the 1400s to the 1800s that, at least in the U.S., should be free from copyright considerations. Arranged into 116 Bible stories, it relies on linked data to populate its database–which means you should be able to use these images for pretty much any purpose.

Visit the Art of the.Bible website.

Linked Data

The site uses Wikidata, a “linked,” or structured, data project from Wikimedia that annotates Wikipedia articles and Wikimedia Commons images with computer-readable data.

Specifically, the site builds on Iconclass, a Dutch system for categorizing (mostly European) artworks based on their subject–for example: Eve takes the fruit from the serpent (or the tree) in the presence of Adam (who may be trying to stop her).

Wikidata has an Iconclass property, so it was just a matter of finding religious art in Wikidata that didn’t have an Iconclass and then making 14,366 edits.

All the data is available in Wikidata; the two SPARQL queries that power the site are for biblical and Christian art.

Most images on Wikimedia Commons don’t have a corresponding Wikidata entry; I estimate that Wikimedia Commons contains at least 50,000 potential biblical artworks that aren’t on Wikidata.

The Frontend

The frontend is a simple, static HTML browser; it’s full of JSON+LD if you’re into that kind of thing.

Google Will Now Answer Your Theological Questions

April 14th, 2018

Google just announced an AI-powered experiment called Talk to Books, which lets you enter a query and find passages in books that are semantically similar to your query, not merely passages that happen to match the keywords you chose. For theology- and Bible-related questions, it often presents an evangelical perspective, perhaps because U.S. evangelical publishers have been eager for Google to index their books.

Here are some questions I asked it, with a sample response (not always the first):

Does God exist? “Creatures may or may not exist; God must exist; He cannot not exist.” — The Catholic Collection.

Why does a good God allow suffering? “Either you somehow deny the world’s suffering (that is, suffering is eventually shown to belong to a higher order of goodness) or else one or more of God’s characteristics (existence, benevolence, omnipotence) are denied.” — A Philosophy of Evil.

When does the rapture happen? “Depending upon one’s view, the rapture occurs either before, during, or after a seven-year period of intense trial and trauma on earth known as the tribulation, as recorded in Revelation 6-19.” — Armed Groups: Studies in National Security, Counterterrorism, and Counterinsurgency.

Where is Jesus now? “Wherever you are as you read these words, he is present.” — And the Angels Were Silent. Some of the other answers, like “He is on the shore of the Sea of Galilee with Andrew and other apostles,” are on the strange side–even in context, the answer is wrong, as this sentence is talking about Peter, not Jesus.

It totally whiffs on Who is Abraham’s father? Rather than interpreting the question and providing a factual answer, it presents a number of passages describing how Abraham is the father of Isaac or of Isaac’s descendants. These passages relate semantically but don’t answer the question.

Answers to 'What is the role of the Holy Spirit' include responses from an NKJV study Bible and Billy Graham.

What Twitterers Are Giving up for Lent (2018 Edition)

February 17th, 2018

Social networking, Twitter, and alcohol are the top three things Twitterers gave up for Lent in 2018.

This year social networking topped the list, followed by Twitter, alcohol, chocolate, and swearing. It was a fairly typical year, with the top five the same as last year (though in a different order)–except for swearing, which came in at #6 last year, behind chips. (Chips had received a boost last year from Theresa May’s vow to give them up; this year they returned to closer to their usual spot.)

This year, 29,609 tweets (excluding retweets) specifically mention giving up something, down substantially from last year’s 73,334. In all, this year the analysis covers 427,810 tweets, down from 694,244 last year.

Relationships

As expected with Valentine’s Day falling on Ash Wednesday this year, relationship-related tweets increased:

Men + boys increased, Valentine's Day + love + being single increased sharply, and women + girls increased slightly.

Plastic

Plastic also jumped substantially this year, boosted by the Church of England’s suggestion that followers give up various forms of plastic for Lent.

Plastic increased to nearly 1% of tweets this year.

Fortnite

New to the list this year is Fortnite, a Hunger Games-style video game:

“It’s all they talk about,” said Glen Irvin, a teacher coach at a high school in Sauk Rapids, Minn., of “Fortnite”-playing students. “The only other game I’ve ever heard kids get this passionate about is ‘Minecraft.’”

Fortnite drastically outperformed Minecraft this year.

Juuling

Also new this year is juuling, a slick and covert way to vape:

Resembling a flash drive, Juul conveys a sense of industry — you’re Juuling into your MacBook Air while you are cramming for your test on Theodore Dreiser and thinking about trigonometry — and it is so easy to conceal that, as one mother explained to me, she failed to notice that her daughter was vaping in the back seat of the car as she was driving.

Giving up juuling this year was nearly half as popular as giving up smoking:

Vaping is a distant third place.

Shootings

Two newcomers to the list this year are #30, guns, and #88, mass shootings. These tweets reflected a shooting at a Florida high school on Ash Wednesday.

The relevant topics jumped

Donald Trump

Donald Trump fell this year from #22 to #67, sandwiched between hope and procrastination.

Percentagewise, tweets related to President Trump fell by about two-thirds.

Tide Pods

Finishing just out of the top 100 this year are Tide Pods, which people keep eating for some reason.

Hopefully this is a one-year wonder.

Fast Food

Chick-fil-A surged to near-parity with McDonald’s, while Chipotle this week decided to deal with its Taco Bell parity by hiring Taco Bell’s former CEO.

Meanwhile, In-N-Out lost its momentum from last year.

Snack Food

Have Hot Cheetos finally plateaued?

Hot Cheetos were identical to last year.

Emojis

This year 4,667 tweets (16%) contained at least one emoji, down from 19% last year. The most-popular emojis were: 😂 😭 ♀ 😩 🙃 🙏 ✌ 😅 🙄 ♂.

Retweets

Here’s the most-retweeted Lent post this year, with over 71,000 retweets. I’m not totally sure why. (All the rest of the data on this page excludes retweets.)

Top 100 Things Twitterers Gave Up for Lent in 2018

Rank Word Count Change from last year’s rank
1. Social networking 1,329 +1
2. Twitter 1,215 +2
3. Alcohol 1,105 -2
4. Chocolate 1,035 -1
5. Swearing 549 +1
6. Meat 531 +6
7. Sweets 499 +3
8. Soda 441 0
9. Coffee 387 +2
10. Fast food 380 -1
11. Lent 373 +2
12. Facebook 342 +9
13. Sex 315 +6
14. Bread 267 +2
15. School 256 -8
16. Chips 222 -11
17. Snapchat 216 +34
18. Beer 193 -3
19. You 189 +1
20. Men 189 +35
21. Plastic 188 +122
22. Sugar 185 -5
23. Boys 165 +2
24. Candy 162 +7
25. Valentine’s Day 157 +130
26. Work 145 -2
27. College 145 -13
28. Negativity 144 +32
29. Instagram 143 +13
30. Guns 141 +126
31. Life 139 -13
32. Marijuana 132 +1
33. Junk food 130 -6
34. Religion 130 -8
35. Giving up things 112  
36. Starbucks 111 -2
37. Red meat 108 +12
38. Cheese 106 -6
39. Catholicism 105 -4
40. Pizza 104 -11
41. Smoking 100 -11
42. Love 100 +96
43. Wine 93 -3
44. Carbs 91 0
45. Me 89 -7
46. Fortnite 87  
47. Lying 84 +25
48. Dairy 81 +13
49. Homework 78 -21
50. Rice 77 -7
51. Booze 76 +12
52. Fried food 75 -7
53. Ice cream 74 -17
54. Complaining 72 +14
55. Cookies 69 -18
56. Single use plastic 68 +100
57. Shopping 68 -11
58. People 66 -11
59. Caffeine 65 +11
60. Stuff 60 -10
61. Masturbation 59 +3
62. Liquor 58 -5
63. F***boys 58 -24
64. Takeout 57 -4
65. Sobriety 57 -9
66. Hope 57 -43
67. Donald Trump 56 -46
68. Procrastination 56 -13
69. Virginity 55 -21
70. McDonald’s 55 -8
71. Hot Cheetos 55 -5
72. French fries 53 -20
73. Netflix 53 -8
74. Fizzy drinks 49 +3
75. Chick Fil A 48 +4
76. Eating out 48 -10
77. Makeup 47 -32
78. Porn 47 +21
79. Myself 45 -3
80. Juuling 45  
81. Him 44 -7
82. Pasta 44 -3
83. Desserts 41 -14
84. Food 40 -25
85. Coke 40 -14
86. Pork 39 +17
87. Dating 38 +23
88. Mass shootings 38  
89. Sleep 38 -16
90. Breathing 37 -47
91. Boba 37 +3
92. Being single 36 +22
93. Cake 36 -6
94. My will to live 36 -36
95. Pancakes 36 -15
96. The presidency 35 -43
97. Online shopping 32 -15
98. Tea 31 +10
99. Brexit 30 +27
100. This 30 -5
101. TV 30 -5

Top Categories

Unlike previous years, no non-political celebrities inspired large numbers of people to give them up.

Rank Category Number of Tweets
1. food 6,702
2. technology 3,556
3. habits 2,034
4. smoking/drugs/alcohol 2,027
5. relationship 1,339
6. irony 946
7. school/work 714
8. sex 568
9. religion 404
10. politics 252
11. generic 224
12. possessions 155
13. entertainment 149
14. shopping 147
15. health/hygiene 125
16. money 94
17. sports 53
18. weather 21
19. clothes 14

Media Coverage

The Lent Tracker received some media attention this year:

Track in Real Time What People Are Giving Up for Lent in 2018

February 12th, 2018

See the top 100 things people are giving up for Lent in 2018 on Twitter, continually updated until February 17, 2018. You can also use the Historical Lent Tracker to see trends since 2009, though 2018 is still in flux, so I wouldn’t draw any conclusions about 2018 yet.

As I write this post, with about 1,500 tweets analyzed, perennial favorites “social networking,” “alcohol,” and “twitter” lead the list. Ash Wednesday coincides with Valentine’s Day this year (and thus Easter with April Fools’ Day), so I expect relationship-related tweets to run higher than usual.

Look for the usual post-mortem on February 18, 2017.

A Blended Account of Palm Sunday

April 9th, 2017

Gospel harmonies have a long history, dating back to the second century, and come in two main varieties:

1. Parallel

Accounts of similar events in different gospels appear in parallel columns so that readers can compare all four accounts side-by-side. This approach allows the distinctive voice of each author to remain, while visually emphasizing continuities and discontinuities–a story found in all four gospels looks much different on the page from a story found in only one. Typically parallels appear at the pericope or story level rather than at the word or verse level. Nearly all gospel harmonies we see today fall into this category.

2. Blended

A blended, or composite, gospel attempts to present the four disparate accounts as a single story, often picking a dominant gospel and using other gospels to fill in gaps. This approach emphasizes the unity of the gospel story while often smoothing over differences small (word choice) and large (chronology of events) among the gospels. It also diminishes the literary structure, purpose, and language of the individual gospel writers. In exchange for these drawbacks, a blended gospel (ideally) gains simplicity and narrative clarity.

The earliest known gospel harmony, the Diatessaron, dates from around 160 and is a blended account. Since the Protestant Reformation, however, parallel column-style harmonies have dominated.

A Digital-First Harmony

A blended digital gospel harmony can overcome many of the shortcomings of a static, print-based blended harmony for two reasons: unlimited space and interactivity.

Unlimited space allows harmonizers to make visible the choices they’re making as they blend accounts. Rather than choosing a single word and omitting variations from other gospels, they can show all the variations and allow the reader to check their work. This approach imports one of the advantages of parallel harmonies: it’s easy to see the similarities and differences among the different gospels. I feel that presenting these variants inline rather than visibly separate–as in different columns–only minimally disrupts the reading flow while giving readers the ability to understand the complexities involved for themselves.

Interactivity addresses three major problems of a blended gospel: which account takes priority, how to arrange the material chronologically, and determining whether different gospels are recounting either the same event with apparent discrepancies or two different events (e.g., Matthew’s sermon on the mount and Luke’s sermon on the plain). The solution in each case: let the reader choose.

In this way, harmonizers are creating less a product and more a system that allows readers to explore the system and draw their own conclusions.

Any blended harmony necessarily dilutes the intent of the original author–adding or omitting details is part of the editing process. However, by making such changes explicit and explorable, an interactive blended harmony can minimize the dilution.

Example: Blended Palm Sunday

A blended account of Palm Sunday.

This blended Palm Sunday account illustrates some of what I discuss above. All variations appear near the related main text. (The extent of your browser’s support of the <ruby> element dictates where the variations appear.) I also added some minimal interactivity: selecting the checkboxes changes the text from the selected gospels to red–in this case, all the text from Matthew is red. You can imagine other interactivity: maybe you can excise certain gospels, or choose which ones receive priority. John, for example, presents the Palm Sunday story in nearly reverse chronological order compared to the other three gospels; rearranging the synoptic narrative to fit John’s account would be an interesting exercise.

This example is just a proof of concept and took a surprisingly long time to put together. I can only imagine that constructing a complete blended harmony of the gospels at this level of detail would involve a large investment of time with no realistic commercial return. Kermit Zarley in 1987 published The Gospels Interwoven, an NIV blended gospel blurbed by Billy Graham; it was out of print a decade later and survives only in print-on-demand form. If a product like that doesn’t find commercial success, the one I’m proposing would find even less. Still, I like to think that this proposal serves as an example of a digital-first product that wouldn’t be possible in print form; it’s a bit ironic that technology could reintroduce and potentially improve the oldest approach to harmonizing the gospels: blended gospels like the Diatessaron.

What Twitterers Are Giving up for Lent (2017 Edition)

March 5th, 2017

A Wordle (wordle.net) of the top 100 things people said they were giving up for Lent this year on Twitter.

This year, alcohol topped the list for the first time; it’s been hovering in the top five for the past few years, last year landing at a then-record #3. Possibly the recent popularity of Dry January (according to the article, 16% of British adults participated in 2016) is carrying over to Lent.

“Chips” cracked the top five this year largely because British Prime Minister Theresa May announced she was giving them up for Lent. This announcement had knock-on effects lower down the list, with “her favourite thing” and “live mice” both coming in at #88. The announcement of the potential closure of a U.K. chip factory the next day led to further jokes. For my U.K. readers, yes, I know you call them crisps (and your “chips” are U.S. “French fries”); I would now tell myself in 2009, when I first started compiling this list, not to combine “chips” and “crisps” into a single line, but it’s too late now.

Donald Trump is a big winner this year, landing at #22, just behind “Facebook” but ahead of “hope.” “The presidency” comes in at #52. In all, there are 1,002 tweets mentioning “Trump,” “President,” and “POTUS,” which is good enough for #10 on the list if we were to combine them all into a single line.

“The dirtiest thing” (#66) refers to a campaign to give up non-renewable energy.

This year, 73,334 tweets (excluding retweets) specifically mention giving up something. This total is up from last year’s 60,000 tweets; I used broader search terms this year (“lent” and “lent2017”) than I have in the past. In all, this year the analysis covers 694,244 tweets, up from 200,000 last year–again, largely because of the broader search terms.

Rank Word Count Change from last year’s rank
1. Alcohol 2,396 +2
2. Social networking 2,148 0
3. Chocolate 2,143 -2
4. Twitter 2,064 0
5. Chips 1,416 +15
6. Swearing 1,395 0
7. School 1,189 -2
8. Soda 1,186 -1
9. Fast food 1,092 +1
10. Sweets 990 -2
11. Coffee 969 -2
12. Meat 909 -1
13. Lent 906 0
14. College 894 +5
15. Beer 888 +8
16. Bread 691 0
17. Sugar 660 -5
18. Life 645 +11
19. Sex 612 -1
20. You 609 -5
21. Facebook 594 -7
22. Donald Trump 520 +62
23. Hope 456 +31
24. Work 442 +3
25. Boys 433 -1
26. Religion 406 +4
27. Junk food 401 -6
28. Homework 393 -6
29. Pizza 373 -12
30. Smoking 296 +5
31. Candy 288 -5
32. Cheese 284 +4
33. Marijuana 267 +6
34. Starbucks 265 -6
35. Catholicism 259 +12
36. Ice cream 249 -5
37. Cookies 227 +1
38. F***boys 220 -13
39. Wine 219 -2
40. Being petty 212 +21
41. Instagram 210 -8
41. Breathing 210 +22
42. Rice 209 0
43. Carbs 202 +5
43. Fried food 202 +6
44. Makeup 201 +2
45. Shopping 190 +3
46. People 189 +4
47. Virginity 185 +12
48. Red meat 184 +3
49. Stuff 180 -5
50. Snapchat 168 -16
51. French fries 166 -6
52. The presidency 164 +82
53. Procrastination 159 +3
54. Men 158 +18
55. Sobriety 156 +5
56. Liquor 155 +6
57. My will to live 154 +77
58. Food 150 -15
58. Negativity 150 -3
59. Takeout 148 +7
60. Dairy 144 +6
61. McDonald’s 143 -8
62. Booze 141 -4
63. Masturbation 138 -8
64. Netflix 136 -32
64. Hot Cheetos 136 -1
65. Eating out 133 +6
66. The dirtiest thing 132 +28
67. Complaining 130 -10
68. Desserts 126 -16
69. Caffeine 125 -19
70. Coke 124 -9
71. Lying 123 +15
72. Sleep 115 -2
73. Him 114 +3
74. Feelings 108 -22
75. Fizzy drinks 103 -12
76. My job 99 +15
76. Juice 99 +1
76. Chick Fil A 99 -8
77. Pasta 95 -12
78. Pancakes 94 -7
79. Nothing 91 +14
80. Online shopping 89 -17
81. Naps 88 +9
82. Church 87 -1
83. Living 86 +43
84. Memes 83 +27
85. Cake 82 -15
86. My phone 79 -33
87. Stress 78 -14
88. Eating live mice 77  
88. My attitude 77 -10
88. Caring 77 -24
88. Her favourite treat 77  
89. Abbreviations 75 +41
90. Politics 74 +3
90. Sweet tea 74 -2
91. Potatoes 72 0
91. Classes 72 +10
92. Boba 70 +10
93. Christianity 69 -13
94. TV 65 -11
94. Sarcasm 65 -20
95. Taco Bell 63 -20
95. Donuts 63 +6
96. Oxygen 62 +18
96. Porn 62 -24
97. Studying 60 -9
97. My boyfriend 60 +3
97. The gym 60 +8
97. Diet coke 60 -30
98. Everything 59 -11
98. Anxiety 59 +13
99. New Year’s resolutions 58 -20
100. Chipotle 57 -31
100. Pork 57 -16

Fast Food

Chipotle now lands behind even Taco Bell.

In n Out continues its rise.

Snack Food

Hot Cheetos continue their snack-food dominance.

Potato chips are up a little because of Theresa May.

Adulting

It’s a verb now. Or at least a gerund.

Adulting overtakes being an adult this year.

Emojis

Just over 14,000 tweets (19%) included an emoji this year. I haven’t tracked emoji usage before, so I can’t say how that compares to previous years.

Here are the top five emojis used this year, along with the most-popular items given up:

Emoji Tweets Most-popular Given Up
😂 2,428 chocolate, alcohol, twitter
😭 1,154 chocolate, sweets, fast food
😩 889 chocolate, sweets, fast food
🙃 875 chocolate, coffee, fast food
🙄 640 chocolate, alcohol, social media

Conversely, here are the most-popular things given up with tweets that include emojis:

Given up Tweets Most-popular Emojis*
chocolate 793 🍫 🙈 😫
social media 549 ✌ 👋 🙏
alcohol 537 😅 ♀ 😬
twitter 482 ✌ 👋 🙏
sweets 355 😅 🍬 🍫

* Excluding the top-ten emojis for the year.

Retweets

The rest of this data excludes retweets, but here are the three tweets mentioning Lent that drew the most retweets. I feel that this list encapsulates Twitter; not many other top-three lists would include college humor, the pope, and Rick “Never Gonna Give You Up” Astley.

Categories

Here are my categories for the top 740 things people gave up:

Rank Category Number of Tweets
1. food 17,017
2. technology 5,659
3. habits 4,962
4. smoking/drugs/alcohol 4,880
5. irony 3,495
6. school/work 3,470
7. relationship 2,541
8. sex 1,179
9. religion 1,055
10. politics 911
11. generic 679
12. entertainment 447
13. shopping 407
14. health/hygiene 328
15. money 279
16. sports 152
17. possessions 103
18. clothes 64
19. weather 28
20. celebrity 20

Media Coverage

The Lent Tracker received some media attention this year:

  1. Christianity Today
  2. International Business Times
  3. The Sun
  4. Daily Herald
  5. Baptist News
  6. Cleveland.com
  7. Pajamas Media
  8. Catholic News Service

Track in Real Time What People Are Giving Up for Lent in 2017

February 27th, 2017

See the top 100 things people are giving up for Lent in 2017 on Twitter, continually updated until March 4, 2017. You can also use the Historical Lent Tracker to see trends since 2009, though 2017 is still in flux, so I wouldn’t draw any conclusions about 2017 yet.

As I write this post, with about 1,600 tweets analyzed, perennial favorites “social networking,” “alcohol,” and “chocolate” lead the list. My main question, given the current U.S. political climate, is how high Donald Trump will rank: he’s currently vying with smoking and sugar for #24–last year, as a presidential candidate, he finished at #82.

Look for the usual post-mortem on March 4, 2017.

Jesus is not your password

January 6th, 2017

At Christianity Today I have a piece today about bad passwords that Christians use: Beware of Making Jesus Your Password. I’m pretty excited that they kept the line about soccer.

Here I want to share the data behind the piece. The 32 million passwords come from the 2009 RockYou breach, available here. I used rockyou-withcount.txt.tar.gz.

The main list of passwords comes from (1) taking this list, (2) removing non-alphanumeric and leading and trailing numbers, (3) lower-casing the result, and (4) combining the totals. In the raw list, “jesus” is the 103rd most-common password; by normalizing it with these steps, it jumps to #30. The purpose here is to find the core part of the password. It’s good from a security perspective that people add leading and trailing (mostly trailing) numbers to their passwords, but they’re not so relevant here.

The list of “Christian” passwords is based on a different breach of a faith-based website. I pulled a bunch of patterns from passwords that were popular there.

Here’s the data behind the piece:

  1. normalized-passwords.zip. A list of 238,000 passwords following the normalization scheme I describe above. Every normalized password from RockYou that appeared at least ten times is here. Note that there’s extensive swearing.
  2. christian-passwords.txt. All 505 Christian-themed passwords.
  3. verse-passwords.txt. All 295 plausible verse references. Not all of them are actually references: for example, “daniel14” could refer to Daniel 1:4 (or even Daniel 14), but it’s most likely just someone’s name with the number “14” after it. So I don’t include it in the top-25 list that appears at CT.

These are my favorite tweets about it: