diff --git a/processors/networks/image-network.py b/processors/networks/image-network.py
new file mode 100644
index 000000000..123a1189b
--- /dev/null
+++ b/processors/networks/image-network.py
@@ -0,0 +1,146 @@
+"""
+Make a bipartite Image-Item network
+"""
+import json
+
+from backend.lib.processor import BasicProcessor
+
+import networkx as nx
+
+__author__ = "Stijn Peeters"
+__credits__ = ["Stijn Peeters"]
+__maintainer__ = "Stijn Peeters"
+__email__ = "4cat@oilab.eu"
+
+from common.lib.exceptions import ProcessorInterruptedException
+from common.lib.user_input import UserInput
+
+
+class ImageGrapher(BasicProcessor):
+    """
+    Image network
+
+    Creates a bipartite network of images and some attribute of the dataset the
+    images were sourced from
+    """
+    type = "image-bipartite-network"  # job type ID
+    category = "Networks"
+    title = "Bipartite image-item network"  # title displayed in UI
+    description = ("Create a GEXF network file with a bipartite network of "
+                   "images and some data field (e.g. author) of the dataset "
+                   "the images were sourced from. Suitable for use with Gephi's "
+                   "'Image Preview' plugin.")
+    extension = "gexf"  # extension of result file, used internally and in UI
+
+    options = {}
+
+    @classmethod
+    def get_options(cls, parent_dataset=None, user=None):
+        root_dataset = None
+        columns = None
+        if parent_dataset:
+            for parent in reversed(parent_dataset.get_genealogy()):
+                if parent.get_columns():
+                    root_dataset = parent
+                    break
+            columns = root_dataset.get_columns()
+
+        return {
+            "column": {
+                "help": "Dataset field",
+                "type": UserInput.OPTION_TEXT,
+                "default": "id"
+            },
+            "image-value": {
+                "help": "Image node label",
+                "type": UserInput.OPTION_CHOICE,
+                "options": {
+                    "filename": "Image file name",
+                    "url": "Image URL"
+                },
+                "tooltip": "The image node label will have this value. Depending on the network visualisation software "
+                           "you use, one or the other is required to display the images as nodes."
+            },
+            **({
+                   "column": {
+                       "help": "Dataset field",
+                       "type": UserInput.OPTION_CHOICE,
+                       "options": {
+                           column: column
+                           for column in columns}
+                   }
+               } if columns else {})
+        }
+
+    @classmethod
+    def is_compatible_with(cls, module=None, user=None):
+        """
+        Allow processor to run on images downloaded from a dataset
+
+        :param module: Module to determine compatibility with
+        """
+        return module.type.startswith("image-downloader")
+
+    def process(self):
+        column = self.parameters.get("column")
+        metadata = None
+        for file in self.iterate_archive_contents(self.source_file, filename_filter=[".metadata.json"]):
+            with file.open() as infile:
+                try:
+                    metadata = json.load(infile)
+                except json.JSONDecodeError:
+                    pass
+
+        if not metadata:
+            return self.dataset.finish_with_error("No valid metadata found in image archive - this processor can only "
+                                                  "be run on sets of images sourced from another 4CAT dataset.")
+
+        id_file_map = {}
+        for url, details in metadata.items():
+            for item_id in details.get("post_ids", []):
+                id_file_map[item_id] = url if self.parameters.get("image-value") == "url" else details["filename"]
+
+        root_dataset = None
+        for parent in reversed(self.dataset.get_genealogy()):
+            if parent.get_columns():
+                root_dataset = parent
+                break
+
+        if not root_dataset:
+            return self.dataset.finish_with_error("No suitable parent dataset found - this processor can only "
+                                                  "be run on sets of images sourced from another 4CAT dataset.")
+
+        network = nx.DiGraph()
+        processed = 0
+        for item in root_dataset.iterate_items():
+            self.dataset.update_progress(processed / root_dataset.num_rows)
+            processed += 1
+            if processed % 100 == 0:
+                self.dataset.update_status(f"Processed {processed:,} of {root_dataset.num_rows:,} item(s)")
+
+            if self.interrupted:
+                raise ProcessorInterruptedException()
+
+            if item.get("id") not in id_file_map:
+                continue
+
+            from_node_label = item.get(column)
+            from_node = f"{column}-{from_node_label}"
+            to_node_label = id_file_map[item.get("id")]
+            to_node = f"image-{to_node_label}"
+
+            if from_node not in network.nodes:
+                network.add_node(from_node, label=from_node_label, category=column)
+
+            if to_node not in network.nodes:
+                network.add_node(to_node, label=to_node_label, category="image", image=to_node_label)
+
+            edge = (from_node, to_node)
+            if edge not in network.edges():
+                network.add_edge(*edge, frequency=0)
+
+            network.edges[edge]["frequency"] += 1
+
+        self.dataset.update_status("Writing network file")
+        nx.write_gexf(network, self.dataset.get_results_path())
+        self.dataset.finish(len(network.nodes))