Anchors
| Anchor text | Ref. domains ▾ | Top DR | Ref. pages | Links to target | Dofollow links |
|---|---|---|---|---|---|
| Institute of Transportation Studies | 5 | — | 0 | 575 | 575 100% |
| Ride sharing | 2 | — | 0 | 2 | 2 100% |
| Berkely Highway Laboratory | 2 | — | 0 | 2 | 0 0% |
| Institute for Transportation Studies | 1 | — | 0 | 1 | 1 100% |
| study at the University of Berkeley | 1 | — | 0 | 1 | 1 100% |
| study | 1 | — | 0 | 1 | 1 100% |
| https://tinyurl.com/352cfwdm | 1 | — | 0 | 3 | 3 100% |
| internships | 1 | — | 0 | 1 | 1 100% |
| kutatása | 1 | — | 0 | 1 | 0 0% |
| Juan Carlos Muñoz | 1 | — | 0 | 1 | 1 100% |
| coauthored a book | 1 | — | 0 | 1 | 1 100% |
| 1 | — | 0 | 1 | 1 100% | |
| state’s ridership forecasts “are not reliable.” | 1 | — | 0 | 1 | 1 100% |
| UC Campus Profile | 1 | — | 0 | 1 | 1 100% |
| California Partners for Advanced Transportation Technology (PATH) | 1 | — | 0 | 1 | 1 100% |
| http://www.its.berkeley.edu/ | 1 | — | 0 | 1 | 0 0% |
| 1 | — | 0 | 1 | 1 100% | |
| Review of “Bay Area/California High-Speed Rail Ridership and Revenue Forecasting Study” | 1 | — | 0 | 1 | 1 100% |
| common rule of thumb | 1 | — | 0 | 2 | 2 100% |
| news | 1 | — | 0 | 1 | 1 100% |
| University of California, Berkeley Transportation Systems Lab | 1 | — | 0 | 1 | 1 100% |
| 1 | — | 0 | 1 | 1 100% | |
| UC Berkeley Institute of Transportation Studies | 1 | — | 0 | 1 | 1 100% |
| ITS | 1 | — | 0 | 1 | 1 100% |
| Berkeley Transportation Letter. | 1 | — | 0 | 1 | 1 100% |
| Alexey Pozdnukhov: Smartphones and Smart Cities | ITS.Berkeley.edu | 1 | — | 0 | 1 | 1 100% |
| The Institute of Transportation Studies | 1 | — | 0 | 1 | 1 100% |
| http://www.its.berkeley.edu/publications/ITSReview/ITSReview.html | 1 | — | 0 | 1 | 1 100% |
| PATH study | 1 | — | 0 | 1 | 1 100% |
| Institute of Transportation Studies | 1 | — | 0 | 1 | 1 100% |
| Institute of Transportation Studies (ITS) | 1 | — | 0 | 1 | 1 100% |
| Bott's Dots | 1 | — | 0 | 1 | 0 0% |
| ITS Berkeley | 1 | — | 0 | 1 | 1 100% |
| 58% of intersections have crosswalks | 1 | — | 0 | 1 | 1 100% |
| Historical Transportation Development | 1 | — | 0 | 1 | 1 100% |
| Roundtable on Sustainable Biofuels | 1 | — | 0 | 1 | 0 0% |
| Institute of Transportation Studies, University of California at Berkeley, USA | 1 | — | 0 | 1 | 1 100% |
| UC Berkeley Transportation Sustainability Research Center | 1 | — | 0 | 1 | 1 100% |
| here | 1 | — | 0 | 1 | 1 100% |
| Electric Two-Wheelers In China:Analysis Of Environmental … | 1 | — | 0 | 1 | 1 100% |
Frequently Asked Questions
What anchor texts are used to link to its.berkeley.edu?
This page shows all anchor texts found in backlinks pointing to its.berkeley.edu, sorted by the number of referring domains using each anchor. Anchor texts range from branded terms (like the domain name itself) to keyword-rich phrases that describe the linked content. The distribution of anchor texts reveals how other websites perceive and describe its.berkeley.edu.
What is anchor text?
Anchor text is the visible, clickable text in a hyperlink. Search engines use anchor text as a signal to understand what the linked page is about. For example, if many sites link to a page using the anchor text "best running shoes," search engines infer that the page is relevant to that topic. Anchor text appears in several forms: exact-match (contains target keywords), branded (uses the company or domain name), generic (like "click here"), and naked URLs.
Why is anchor text analysis important for SEO?
Anchor text analysis helps identify potential SEO risks and opportunities. A natural backlink profile has diverse anchor texts including branded terms, generic phrases, and topic-relevant keywords. Over-optimization, where too many backlinks use the same exact-match keyword anchor, can trigger search engine penalties. Conversely, understanding which anchors drive the most authority (measured by referring domain count and DR) helps prioritize link building efforts.
How many unique anchor texts does its.berkeley.edu have?
The anchor text report for its.berkeley.edu displays all distinct anchor texts grouped by their hash. Each row shows how many unique referring domains use that anchor, the total number of links, and the dofollow percentage. A high number of unique anchors generally indicates a healthy, natural backlink profile with diverse link sources.