OpenBible.info Blog

Automatically Deciphering Ugaritic

July 1st, 2010

Let’s say you have text in front of you written in a language you don’t read–worse, no one has understood the language for thousands of years. How can you begin to understand it? MIT researchers have created a way to for a computer to decipher Ugaritic in a few hours without knowing anything about the language besides its general similarity to Hebrew.

One of the researchers says:

The decipherment of Ugaritic [in the mid-twentieth century] took years and relied on some happy coincidences — such as the discovery of an axe that had the word “axe” written on it in Ugaritic. “The output of our system would have made the process orders of magnitude shorter.”

I love that someone felt the need to write “axe” on an axe. Maybe it was the original brand name.

I’m most curious whether the program can help crack the Minoan language on Linear A.

Incidentally, the article What’s Ugaritic Got to Do with Anything? explains why Ugaritic is important to understanding the Hebrew of the Old Testament.

Via.

Posted in Linguistics | Comments Off on Automatically Deciphering Ugaritic

Church Names in the U.S.

June 5th, 2010

If you were to name a church, how would you go about it? Let’s see how people have named churches in the U.S. by looking at a random sample of 300,000 church names gathered using the Yahoo! Local Search API.

The Word “Church”

You might start with the word “church” in your name. About 2/3 of churches in the dataset have the word “church.” (The number of churches with the word “church” in reality is higher, as the dataset often truncates names.) Other popular nouns: center, fellowship, chapel, assembly, ministries (or ministry), temple, tabernacle, and iglesia.

Most Common Words in Church Names

Here’s a wordle of the most common words that appear in church names (excluding the word “church”):

Most Common Words in Church Names, Excluding Denominations

Denominations overpower the raw list. Here’s a wordle of the same data without denomination names:

Full Church Names

Here are the most common church names in the U.S. Also download the top 1,000 church names in the U.S. (29 KB Excel document), covering 95,000 churches, if you want more information.

Church Name	Churches
first baptist church	5,115
church of christ	2,854
first united methodist church	2,149
first presbyterian church	1,960
united methodist church	1,488
seventh-day adventist church	1,478
first christian church	1,309
calvary baptist church	1,197
church of the nazarene	915
trinity lutheran church	892
salvation army	867
first assembly of god	744
church of god	677
faith baptist church	663
st john’s lutheran church	601
grace baptist church	600
first congregational church	575
assembly of god church	565
new hope baptist church	540
zion lutheran church	523

Saints

The word “St.” (Saint) is common in more traditional churches, such as Catholic, Episcopalian, and Lutheran. Here are the most popular saint names used for churches:

Saint	Churches
John	3,713
Paul	3,210
Mary	1,832
Peter	1,362
James	1,270
Joseph	1,153
Mark	1,062
Luke	1,053
Andrew	789
Matthew	724
Stephen	582
Michael	532
Francis	530
Thomas	511
Patrick	431
Anthony	381
George	329
Ann(e)	282
Nicholas	253
Elizabeth	220

Mountains

Mountains and hills are common names for churches. I suspect that “Spring Hill” and the assorted “Pleasant”s come from the city names where the churches stand.

Mountain	Churches
mt zion	1,587
mt olive(t)	1,122
mt calvary	619
mt carmel	528
mt pleasant	475
pleasant hill	394
mt moriah	329
mt sinai	316
zion hill	200
mt pisgah	191
mt nebo	139
mt tabor	136
mt pilgrim	112
mt hope	108
mt gilead	95
mt bethel	90
spring hill	90
mt hermon	85
mt lebanon	74
mars hill	59

Denominations

Here are the most-common two-word phrases (including denomination names) used in some of the more popular denominations. “First” appears in 12% of Baptist church names, 10% of Methodist church names, only 3% of Lutheran church names, and fully 21% of Presbyterian church names.

Baptist	Methodist	Lutheran	Presbyterian
first baptist	united methodist	trinity lutheran	first presbyterian
missionary baptist	first united	st john’s	united presbyterian
freewill baptist	chapel united	st paul’s	cumberland presbyterian
grove baptist	free methodist	evangelical lutheran	korean presbyterian
calvary baptist	trinity united	zion lutheran	westminster presbyterian
hill baptist	memorial united	grace lutheran	covenant presbyterian
zion baptist	st paul	our savior’s	community presbyterian
hope baptist	grace united	faith lutheran	memorial presbyterian
creek baptist	grove united	immanuel lutheran	trinity presbyterian
faith baptist	wesley united	christ lutheran	orthodox presbyterian
mt zion	zion united	peace lutheran	reformed presbyterian
bethel baptist	hill united	redeemer lutheran	grace presbyterian
new hope	christ united	first lutheran	hill presbyterian
grace baptist	bethel united	good shepherd	faith presbyterian
bible baptist	faith united	hope lutheran	hope presbyterian
chapel baptist	hope united	calvary lutheran	christ presbyterian
community baptist	street united	bethlehem lutheran	central presbyterian
mt olive	asbury united	st peter’s	valley presbyterian
memorial baptist	park united	bethany lutheran	creek presbyterian
southern baptist	salem united	messiah lutheran	park presbyterian

Posted in Churches | 5 Comments »

Most Highlighted Bible Passages on Kindle

May 20th, 2010

Ray Fowler analyzes Amazon’s Kindle data to find the most-highlighted Bible passages on Kindle.

Ten of the fourteen verses overlap the thirty most popular verses on Twitter, a higher percentage than I expected.

Posted in Collective Intelligence | Comments Off on Most Highlighted Bible Passages on Kindle

Bible Cross References Visualization

April 16th, 2010

Here’s a visualization of 340,000 Bible cross references:

Larger version (2,000 x 1,600 pixels).

Does anything strike you as intriguing? A few trends jump out at me:

The frequency of dense New Testament streaks in the Old Testament, especially in Leviticus and Deuteronomy; I didn’t expect to see them there.
The loops in Samuel / Kings / Chronicles and in the Gospels indicating parallel stories.
The sudden increased density of New Testament references in Psalms through Isaiah.
The eschatological references in Isaiah and Daniel.
The density of references from the Minor Prophets back to both the Major Prophets and earlier in the Old Testament.
The surprising density of cross references in Hebrew-Jude.
The asymmetry. If verse A cites verse B, verse B doesn’t necessarily cite verse A. I wonder if I should make the data symmetrical.

You can also download the full-size image (10,000 x 8,000 pixels, 75 MB PNG). It’s a very large image that could crash your browser. If you want it, I strongly recommend that you save it to your computer rather than trying to open it in your browser.

This visualization uses data from the Bible Cross References project. I used PHP’s GD library to create the graphic.

Inspired by Chris Harrison and Christian Swinehart’s wonderful Choose Your Own Adventure work.

Posted in Cross References, Visualizations | 6 Comments »

New in Labs: Cross References

April 11th, 2010

Browse 340,000 Bible cross references. Make the list better by voting on relevant or irrelevant verses.

For example, try Philippians 4:13 (“I can do all things through Christ who strengthens me”) or Isaiah 40:31 (“They shall mount up on wings like eagles”).

The interface is about as bare-bones as it gets: there’s a list of cross references for a single Bible verse, sorted by relevance (i.e., votes). You can browse to related verses, vote on whether each cross reference is relevant, and see (on external sites) the verses in different translations. It also prints nicely. There’s no way to suggest new cross references, though I may add that feature if there’s demand.

The data comes primarily from The Treasury of Scripture Knowledge (TSK) but blends other data, including the Topical Bible and Twitter Bible Search. All the copies of TSK on the web seem to descend from one source; I did some basic cleaning of the data and extracted the references. Then I blended the other data to weight some cross references more highly than others—that’s where the initial vote counts come from. (Incidentally, I only count around 380,000 cross references in TSK, lower than the usual count of 500,000 cross references you find when people talk about TSK. The lower number of cross references on this site–340,000–comes mostly from removing duplicates and combining adjacent verses.)

The 340,000 cross references in this data are a substantial number–most cross reference systems in print Bibles contain 50,000-100,000 cross references. While this list is more comprehensive, the tradeoff is that some of the cross references are less relevant than you find in print Bibles. As people use this site, however, the most-relevant verses should rise to the top.

The main limitation to the data is that the cross references always point from a single verse rather than from a range of verses: in other words, from Matthew 5:3 instead of from Matthew 5:3-11. Broader cross references—references that apply to a complete passage—are therefore missing from the data, limiting its usefulness somewhat.

The lack of an open, high-quality source of Bible cross references on the web has always bewildered me. This project is an attempt to remedy that deficiency. Feel free to download the raw cross-reference data (2 MB .zip, updated regularly with the latest vote counts) and use it in your projects.

Update April 12, 2010: Fred Sanders at Scriptorium Daily has a great introduction to the Treasury of Scripture Knowledge if you want more background on this work.

Posted in Cross References | 2 Comments »

Presentation on Tweeting the Bible

March 26th, 2010

Here’s a presentation I just gave at the BibleTech 2010 conference about how people tweet the Bible:

Tweeting the Bible (BibleTech 2010) from openbibleinfo

Also: PowerPoint, PDF.

I distributed the following handout at the presentation, showing the popularity of Bible chapters and verses cited on Twitter. It displays a lot of data: darker chapters are more popular, the number in the middle of each box is the most popular verse in the chapter, and sparklines in each box show the distribution of the popularity in each chapter. (Genesis 1:1 is by far the most popular verse in Genesis 1, while Genesis 3:15 is only a little more popular than other verses in the chapter.)

Posted in Bible, Twitter, Visualizations | 3 Comments »

Delving into Lent Data

March 7th, 2010

Let’s look a little more at some of the data on what Twitterers are giving up for Lent.

Categories of Things Given up by Location

As I only track in English what people are giving up, there are concentrations in English-speaking countries.

Size indicates the relative number of Twitterers in each country giving up something for Lent.

Categories of Things Given up by State

These visualizations show the differences (or lack thereof) in what people are giving up among U.S. states.

Size indicates the relative number of Twitterers in each state giving up something for Lent. Sorry, Alaska and Hawaii.

The composition of each state’s categories of tweets shows mostly minor variations among states. Some states (like Wyoming on the far right) have small numbers of tweets. I would have liked to use opacity or width to indicate this disparity but couldn’t figure out how to do it.

Comparison between 2009 and 2010

This treemap shows how the data changed between 2009 and 2010. The size of the box shows the number of people giving up each category and thing, while color indicates the percentage change from last year: dark blue indicates the steepest drop; dark orange indicates the steepest rise. The second chart shows the same data more conventionally expressed.

About the Visualizations

I created these charts mostly to explore how the new data-analysis software Tableau Public works. One of its claims to fame is that you can publish interactive visualizations to the web, a feature I didn’t take advantage of here. Tableau doesn’t do treemaps, so I used Many Eyes to create the treemap; the closest Tableau equivalent appears below the treemap.

Posted in Lent, Twitter, Visualizations | Comments Off on Delving into Lent Data

What Twitterers Are Giving up for Lent (2010 Edition)

February 23rd, 2010

Snow makes the list this year, understandable given the Snowpocalypse and Snowmageddon that gripped much of the Eastern U.S. in the weeks preceding Ash Wednesday. IPods also made the list after the Bishop of Liverpool asked people to consider praying instead of listening to them. This year a celebrity, Justin Bieber, cracks the top 100. He beat out the Jonas Brothers, 64 votes to 11; draw your own conclusions.

The list largely tracks last year’s list. It draws from 40,000 tweets retrieved February 14-20, 2010.

Complete List of the Top 100

Rank	Word	Count	Change from last year’s rank
1.	Twitter	2089	+1
2.	Facebook	1874	-1
3.	Chocolate	1323	0
4.	Alcohol	1258	+1
5.	Swearing	1158	+5
6.	Soda	1126	0
7.	Lent	792	-3
8.	Meat	720	0
9.	Sex	701	+7
10.	Fast food	695	+7
11.	Sweets	627	0
12.	Coffee	445	-5
13.	iPod	437
14.	Candy	325	+18
15.	Religion	305	-6
16.	Catholicism	264	-4
17.	Smoking	254	+5
18.	Junk food	251	+34
19.	Giving up things	241	-6
20.	Beer	241	-5
21.	Chips	234	+24
22.	You	233	+13
23.	Stuff	217	-3
24.	Fried food	199	+33
25.	Red meat	193	+19
26.	Bread	187	+13
27.	Sugar	183	-8
28.	Work	176	-14
29.	Shopping	174	+11
30.	Food	162	-7
31.	Shame	150
32.	Social networking	147	-2
33.	Caffeine	136	-6
34.	Rice	136	+44
35.	Procrastination	127	-11
36.	Internet	126	-11
37.	Cheese	120	+1
38.	Coke	120	+41
39.	Starbucks	119	+14
40.	School	118	+36
41.	Ice cream	118	+13
42.	Booze	117	-21
43.	Texting	114	+28
44.	Masturbation	111
45.	Cookies	110	+11
46.	TV	97	-18
47.	Christianity	96	0
48.	Snow	96
49.	Wine	92	-13
50.	Pizza	91	+12
51.	MySpace	91	+4
52.	Men	90	+31
53.	Giving up	89	-19
54.	Sobriety	89	-13
55.	Liquor	87
56.	Desserts	87
57.	Lint	87	-20
58.	Pancakes	82	-29
59.	Homework	81	+28
60.	Marijuana	80
61.	Diet Coke	80	-28
62.	Hope	78	+15
63.	Virginity	76
64.	French fries	75	-15
65.	Laziness	71	+5
66.	Boys	67
67.	Nothing	67	-19
68.	Carbs	66	-4
69.	Justin Bieber	64
70.	Pork	64
71.	Porn	63	+9
72.	Me	62	0
73.	Sleep	61	-42
74.	Complaining	58	-16
75.	Eating out	58	-8
76.	Jesus	55	-26
77.	McDonald’s	55
78.	Beef	54	+18
79.	Church	54	+6
80.	God	53	-21
81.	Abstinence	53	-39
82.	Cake	52
83.	Negativity	52
84.	Him	49
85.	Juice	47
86.	Celibacy	44	+13
87.	Chicken	42
88.	Lying	42
89.	New Year’s resolutions	42	-29
90.	Sarcasm	42	-39
91.	Snacking	41
92.	My wife	39
93.	Tea	37
94.	iPhone	37
95.	Exercise	36	-6
96.	Sweet tea	35
97.	People	35
98.	Vegetables	34
99.	Pasta	33
100.	Self control	33

Image created using Wordle.

Posted in Lent, Twitter | 3 Comments »

Videogames as Time Travel

January 12th, 2010

Melik Kaylan writes in today’s Wall Street Journal about how the detailed historical settings in the videogame Assassin’s Creed II allow the player to time-travel to Renaissance Italy (link works now but may not always):

[T]he game is set in Florence, Venice and Rome over a number of decades leading up to the year 1499. The game’s producer-authors… labored lovingly to re-create the environs as exactly as possible. They hired Renaissance scholars to advise on period garb, architecture, urban planning, weaponry and the like. They took tens of thousands of photographs of interiors and streets. They used Google Earth liberally to piece together the ground-up and sky-down perspectives through which the action flows…. The hazy colors and the distant sound of river birds are uncannily correct. Nowadays, the tourist hordes can blot out all sense of history. Once you’ve navigated it on AC2, when you visit the Ponte Vecchio in person the illusion persists of a highly intensified sense of place. In other words, the video brings the place sharply back to life.

Recreating history comes at a price: the budget for the game is something north of $20 million. I hope that the publishers will find a way to put some of their investment to educational use; I for one would love to visit Renaissance Italy without having to assassinate people once I get there.

Someday I hope to see a recreation of ancient Jerusalem this detailed, though I can’t imagine what kind of game could justify the pricetag. In the future, maybe the cost of creating virtual time travel will drop far enough to be within reach of small schools, companies, or individuals.

(Note: I haven’t played the game and don’t intend to. As you might guess from the title, it appears to involve lots of killing. If you’re OK with seeing that kind of thing, on YouTube one of the developers walks through some of the gameplay.)

The main character in Assassin’s Creed II surveys a detailed Renaissance urban landscape.

Posted in Virtual Reality | 2 Comments »

New Feature: Search for Bible Verses on Twitter

November 30th, 2009

Search over 1.2 million Bible verses on Twitter–nearly every tweet that has mentioned a Bible verse since April 2009. You can also see a list of the most popular verses on Twitter over the past few hours (“Trending Verses”).

This project uses several APIs from Twitter and is still in a beta stage. It could evolve in several directions, but I want to see how people use it before developing it further.

It’s not quite realtime, but the most recent tweet is rarely more than a few minutes old.

Behind the scenes, it processes tweets to try to ensure their relevance; it has about a 92% accuracy rate based on a training corpus of around 45,000 tweets. Use the “relevant” and “not relevant” buttons in the interface if you see a tweet that you think should or shouldn’t belong. (I’m mostly interested in the latter, but it seems weird not to have both–like Facebook’s lack of an unlike button.)

It currently uses Logos RefTagger to link the Bible references in the tweets.

Feel free to leave a comment here if you have a feature idea or want to make any suggestions.

Edit February 2016: This feature is no longer available; with over 200 million tweets, it’s just too much data to serve reliably. Instead, the latest tweets are visible.

Posted in Twitter | 3 Comments »

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